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Methodology

Where our numbers come from

Our calculators give planning-stage estimates. This page shows what they are built on: the public and private-market sources behind every number, the dates the data was taken, and where we have made a modelling choice rather than quoted a source.

Sources reviewed July 2026.

Scope

What the calculators estimate, and what they do not

The calculators are built to start a conversation, not to close one. It helps to be precise about the line between the two.

What they give you

  • A planning-stage enterprise value range for an operating company, built from its revenue, profitability, size, industry, and country.
  • An indicative senior-debt style borrowing capacity, expressed as a range of debt to EBITDA.
  • A sense of how those numbers move with company size, growth, and geography.

What they are not

  • A formal valuation, fairness opinion, or audit.
  • A binding lender offer or a committed financing term sheet.
  • The price a specific buyer will pay, which depends on diligence, deal structure, and appetite on the day.
  • A substitute for advice on a live transaction.
How we calibrate

How we calibrate the numbers

Every number traces back to a named source. We keep two things separate, and we tell you which is which.

Sourced levels

Multiple levels that a named third party publishes. For example, GF Data reports an average of 5.9x EBITDA for deals with an enterprise value between $10M and $25M. We quote these with the source and the date.

Alehar-calibrated estimates

Any value we smooth, interpolate, or index to a reference point. No public source publishes a revenue-indexed size curve, an early-stage multiple by growth tier, or a single factor per country. Where we build one, we label it as an Alehar calibration and show the sourced levels it was built from.

The structure of the calculator, a smooth size curve, per-country factors, and growth tiers, is an Alehar modelling choice. The inputs to that structure are sourced. We do not imply that any third party publishes our grid cell by cell.

One caveat governs everything below. Most public multiple data is either public-company trading multiples, which sit well above what small private companies transact at, or transaction data quoted on different earnings bases: seller’s discretionary earnings for the smallest businesses, EBITDA above roughly $2M. A small private company does not receive a public-company multiple, and every reference below already accounts for that.

Company size

How company size changes the multiple

The single largest driver of a small company’s multiple is its size. As revenue falls, the multiple falls with it, and below roughly $2M in revenue the market prices on seller’s discretionary earnings rather than EBITDA. The curve below indexes each revenue point to a lower-middle-market anchor at $20M, where a business trades around a mid-single-digit to high-single-digit EBITDA multiple. It is an Alehar calibration built from the sourced levels in the last column.

RevenueFactor vs $20M anchorWhat sits behind it
$100K0.35Micro and Main Street floor. BizBuySell reports a median near 2.6x SDE and 0.69x revenue, and little of the value transfers to a new owner.
$500K0.44Small owner-operated business. IBBA segments below $1M transact around 2.3x to 2.5x SDE.
$1M0.52BizBuySell’s median deal sits here, at about 2.6x SDE and 0.69x revenue.
$2M0.62The point where the market shifts from pricing SDE to pricing EBITDA, as a buyer begins to assume a hired manager rather than an owner-operator.
$5M0.78GF Data reports 5.5x EBITDA for deals from $1M to $5M. A $5M-revenue business typically closes closer to 4x to 5x, not the full lower-middle-market multiple.
$10M0.90GF Data reports 5.9x EBITDA for the $10M to $25M bucket, and IBBA puts the $5M to $50M range near 6.5x.
$20M1.00The lower-middle-market anchor. GF Data’s $10M to $25M bucket at 5.9x and First Page Sage’s full-year 2025 average of 7.2x set the reference point.
$50M1.10Larger lower-middle-market deals earn a modest premium. GF Data reports 6.6x for $25M to $50M and 8.7x for $50M to $100M.

The factor is a relative multiple, not a multiple itself. It scales the anchor up or down. The curve is smooth by construction, which avoids sharp jumps at round-number revenue thresholds.

Early-stage

The early-stage approach

For recurring-revenue and software businesses below about $5M in revenue, we price on ARR or trailing revenue rather than EBITDA, because these companies often reinvest most of their profit into growth. The market now prices them on profitability, net revenue retention, and the Rule of 40 rather than on growth rate alone, so no source publishes a clean multiple for a specific growth band. The tiers below use growth as the visible proxy a founder can self-report, anchored to sourced revenue-multiple levels. They are an Alehar calibration.

Growth rateARR multipleWhat sits behind it
Under 30%2.0-3.0xAcquire.com reports a median near 2.6x trailing revenue, and Aventis puts the first quartile at 2.4x. Slow-growth small SaaS sits at the bottom of the marketplace range.
30% to 60%3.0-4.5xAventis reports a current median near 3.1x and a long-run median of 4.5x. SaaS Capital predicts about 4.8x for a bootstrapped company.
60% to 100%4.5-6.5xWindsor Drake puts equity-backed high-growth SaaS at 5x to 8x, lifted by strong retention.
Over 100%6.5-9.0xSaaS Capital reports 7x to 9x ARR for companies with a Rule of 40 above 50 and net revenue retention above 120%.

The profit floor

~3.9x

For a profitable small software business, the profit multiple is often the more conservative number. Acquire.com reports a median SaaS profit multiple near 3.9x. Where that figure is lower than the revenue-based one, we treat it as the binding one.

These ranges assume genuine recurring revenue. Retention and profitability can move a business up or down a full tier.

Geography

Country adjustments

We apply one factor per country, flat across industries, and we are explicit about what each factor rests on. Some are informed by country risk premiums, a cost-of-capital adjustment that theory applies to every industry equally. Others reflect market liquidity and the depth of the local buyer pool, not risk. We do not claim a separate factor for each country-and-industry pair, because the public data is too noisy to support one honestly.

CountryFactor vs United StatesWhat the factor rests on
India0.78Risk-premium-informedThe country risk premium implies roughly 0.75, so the factor sits close to the theory.
Philippines0.75Risk-premium-informedThe country risk premium implies roughly 0.78.
United Kingdom0.95Risk-premium-informedThe country risk premium implies roughly 0.94.
Saudi Arabia0.83Cautious calibrationRisk premium alone implies roughly 0.94. We hold the factor lower as a deliberate caution, not because of country risk.
United Arab Emirates0.85Cautious calibrationRisk premium alone implies roughly 0.95. Held lower as a deliberate caution.
Singapore0.88Liquidity and market-depthRated Aaa, so country risk does not justify a discount below the United States. The factor reflects a smaller local exit market and buyer pool.
Netherlands0.91Liquidity and market-depthRated Aaa. Reflects buyer-pool depth and exit-market size, not country risk.
Germany0.93Liquidity and market-depthRated Aaa. Reflects buyer-pool depth and exit-market size, not country risk.
United States1.00AnchorThe reference point for every other factor.

We flag this plainly. Singapore, the Netherlands, and Germany carry no country risk premium above the United States, so nothing about their credit risk justifies a discount. Their factors below 1.0 reflect liquidity and buyer depth, and we label them that way rather than presenting them as risk.

Renewable energy

The renewable-energy split

Renewable energy does not fit one corporate EBITDA multiple, so we split it in two.

Services and developers

Companies with real operating earnings: engineering, procurement and construction, operations and maintenance, and developers who build and rotate assets. Corporate EBITDA logic applies. Public renewable companies traded around 11x to 16x EV/EBITDA through 2024 to 2026. After a private and size discount, a small private services business sits around 5x to 9x, with a mid near 7x. This range is an Alehar calibration off the public band.

Contracted and project-finance assets

Operating solar or wind with a power purchase agreement, project-level debt, or an SPV structure is not valued on a business EBITDA multiple. The market values it on contracted cash flows and capacity. As an indication, operating assets with long-term PPAs transact around $1.0M to $1.8M per MW, and investors underwrite to a levered equity IRR of roughly 8% to 12% and a debt-service coverage ratio. For a project-level figure, the calculator points you to a direct conversation rather than returning a multiple.

Debt capacity

The debt calculator

The debt calculator returns an indicative senior-debt style capacity, expressed as a range of debt to EBITDA. It is deliberately conservative. It reflects the senior leverage a lender might extend to a stable lower-middle-market business, roughly 1.5x to 3.1x depending on country and industry, and lines up with GF Data and Calder lower-middle-market senior leverage. It is not the higher leverage seen in sponsor-backed private-credit deals, and it is not a lender commitment. Country differences are applied as a single, modest adjustment to a global benchmark, which is an internal heuristic rather than a separately sourced market figure for each country.

Disclaimer

The full disclaimer

These outputs are indicative planning estimates, not a formal valuation, fairness opinion, lender offer, or investment recommendation. Alehar calibrates the calculator from maintained lower-middle-market industry benchmarks, public-company trading-multiple datasets such as Damodaran/NYU Stern, selected private-market M&A and SaaS datasets, and middle-market lending reports such as GF Data; we then adjust for company size, growth, profitability, business model, geography, asset base, and debt-service capacity. Actual valuation and debt capacity can move materially based on buyer appetite, revenue quality, customer concentration, working capital, management depth, lender policy, and transaction structure, so the result should be used as a conversation starter before a properly diligence-backed process.

Disclaimer

References

Sources

Every figure on this page and in the calculators traces to one of the sources below. Each entry notes what we take from it and the date of the data.

SourceWhat we take from itAs of
GF Data, The Size Premium Returns to 2.8xEBITDA multiples by enterprise-value bucket for private-equity-sponsored deals.First nine months of 2025
IBBA / M&A Source Market PulseMedian transaction multiples by market segment, and the SDE-to-EBITDA transition near $2M.Q3 2025
BizBuySell Insight ReportMain Street median sale price, cash-flow (SDE) and revenue multiples.Full-year 2025 and Q1 2026
First Page SageEBITDA multiples for small business and by industry.2025
Acquire.com Biannual Acquisition Multiples ReportSaaS profit and revenue multiples for businesses below $10M enterprise value.January 2026
Aventis Advisors, SaaS Valuation MultiplesPrivate SaaS M&A EV/Revenue and EV/EBITDA, 2015 to 2026.March 2026
SaaS Capital Index and benchmarkingPublic SaaS index and private benchmarks, including net revenue retention and Rule of 40 effects.2026
Windsor Drake, SaaS Valuation MultiplesSaaS multiples by enterprise-value band and company type.February 2026
Damodaran / NYU Stern datasetsPublic-company EV/EBITDA, EV/Sales, and country risk premiums by region.January 2026
Finerva, Green Energy and RenewablesRenewable-energy valuation multiples.2026
FTI Consulting, Power, Renewables and Energy TransitionRenewable M&A review and outlook.2025 to 2026
Energy IB, Phoenix Strategy Group, VernimmenProject-finance framing for renewable assets: EV per MW, DSCR, and contracted-cash-flow discounting.2025 to 2026

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