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Altman Z-Score Calculator

Enter a company's financial data to calculate its Altman Z-Score, the most widely cited quantitative model for predicting corporate bankruptcy risk. Choose between the original public-firm model, the private-firm Z' model, or the non-manufacturing Z'' model. Your score is mapped instantly to a Safe, Grey, or Distress zone with a full step-by-step ratio breakdown.

Your details

Altman published separate coefficient sets for each type. Using the wrong model will produce misleading results.
Total assets from the balance sheet (any currency unit, must be consistent).
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Current assets from the balance sheet.
M
Current liabilities from the balance sheet.
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Cumulative retained earnings from the equity section. Can be negative for companies with a history of losses.
M
Earnings before interest and taxes (operating income).
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For public firms: shares outstanding multiplied by share price. For private and service firms: total book equity from the balance sheet.
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Total liabilities from the balance sheet (current + non-current).
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Annual net revenues from the income statement.
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Altman Z-ScoreGrey Zone
2.18

The composite financial health score

X1: Working Capital / Total Assets0.14
X2: Retained Earnings / Total Assets0.24
X3: EBIT / Total Assets0.12
X4: Equity Value / Total Liabilities0.8
X5: Sales / Total Assets0.8
2.18
Distress<1.81Grey Zone1.81-2.99Safe2.99+

Z-Score of 2.18 places this company in the Grey Zone (moderate bankruptcy risk).

  • Using the public manufacturing model, the Safe threshold is 2.99 and the Distress threshold is 1.81.
  • X1 (Working Capital / Total Assets) = 0.140: positive working capital indicates short-term liquidity is intact.
  • X2 (Retained Earnings / Total Assets) = 0.240: accumulated profits suggest financial resilience.
  • X3 (EBIT / Total Assets) = 0.120: asset productivity is healthy.
  • X4 (Equity / Total Liabilities) = 0.800: liabilities exceed equity, reflecting higher leverage.

Next stepGrey Zone results are ambiguous. Cross-check with current-ratio trends, debt-service coverage, and industry peer comparisons before drawing conclusions.

What is the Altman Z-Score?

The Altman Z-Score is a quantitative model created by NYU Stern professor Edward Altman in 1968 to predict the probability of corporate bankruptcy within two years. Altman derived the formula by applying discriminant analysis to a sample of 66 US manufacturing firms, half of which had filed for bankruptcy. The model combines five financial ratios into a single composite score that separates financially healthy companies from those at high risk of failure. It became one of the most widely replicated models in credit analysis and is still used by banks, investment analysts, and credit-rating agencies as a first-pass screening tool.

The three model variants and when to use each

Altman later published two revised versions to handle contexts the original model was not designed for. The original Z-Score (1968) uses market capitalization in X4 and applies to publicly traded manufacturing companies, with a safe-zone threshold of 2.99. The Z' model (1983) replaces market capitalization with book equity, making it suitable for private manufacturing companies, and uses a lower safe-zone threshold of 2.90. The Z'' model (1993) drops the sales-to-assets ratio (X5) entirely and recalibrates the remaining four coefficients for non-manufacturing and service firms, which tend to have very different asset-turnover profiles. Using the wrong model for a given company produces misleading results: apply the original to a service firm and you will almost certainly get an inflated score.

The five ratios and what they measure

X1 (Working Capital / Total Assets) captures short-term liquidity: a declining or negative ratio signals that the company may struggle to meet near-term obligations. X2 (Retained Earnings / Total Assets) reflects long-run profitability and the extent to which the company has reinvested earnings over its lifetime; young companies and serial loss-makers score poorly here. X3 (EBIT / Total Assets) measures how productively the firm uses its asset base to generate operating income; it is the most important single predictor in the original model. X4 (Equity Value / Total Liabilities) acts as a leverage measure; a falling ratio indicates growing reliance on debt. X5 (Sales / Total Assets) is an asset-turnover ratio; Altman excluded it from the Z'' model because it introduced distortion when comparing service and manufacturing businesses.

Limitations and best-practice use

The Z-Score was calibrated on 1960s US manufacturing data, which limits its direct applicability to modern companies, especially high-growth technology firms or financial institutions. It is a point-in-time snapshot and can move sharply when a large acquisition changes total assets, when retained earnings are restated, or when share prices shift. Analysts treat it as a supplement to, not a replacement for, qualitative judgment, cash-flow modeling, and peer comparison. A score in the Grey Zone in particular should trigger deeper analysis rather than a binary pass/fail decision. Regulatory guidance in some jurisdictions requires that credit models be back-tested and periodically recalibrated for the portfolio they are applied to.

Altman Z-Score zones by model

ModelSafe ZoneGrey ZoneDistress Zone
Public manufacturing (Z) > 2.99 1.81 - 2.99< 1.81
Private manufacturing (Z') > 2.90 1.23 - 2.90< 1.23
Non-manufacturing / service (Z'') > 2.60 1.10 - 2.60< 1.10

Thresholds differ across the three model variants. A score near the boundary should be treated as uncertain.

Frequently asked questions

What Z-Score is considered safe?

For public manufacturing companies the threshold is above 2.99. For private manufacturing companies the safe boundary is above 2.90. For non-manufacturing and service companies the safe boundary is above 2.60. Scores below these ranges do not guarantee bankruptcy, but they indicate elevated financial stress that warrants investigation.

What is the Grey Zone in the Altman model?

The Grey Zone is the range between the distress threshold and the safe threshold where predictions are statistically ambiguous. For the original public model this is 1.81 to 2.99. A company in the Grey Zone is neither clearly healthy nor clearly at risk; misclassification rates are highest in this range, so it should prompt additional due diligence rather than a firm conclusion.

Can the Altman Z-Score be used for banks and financial companies?

No. The original model explicitly excluded financial companies because their leverage profiles are structurally different: a bank typically has a debt-to-equity ratio that would place any non-bank in the Distress Zone. Separate models have been developed for financial institutions. If you are analyzing a bank or insurance company, use a sector-specific credit model instead.

Does the Z-Score work for technology companies?

With caution. Many technology firms have low asset bases relative to revenue, which inflates the asset-turnover ratio (X5) and can produce an artificially high Z-Score. Young tech companies also often have negative retained earnings, which depresses X2. The Z'' model designed for non-manufacturing companies is a better starting point, but the score should always be benchmarked against sector peers rather than used against absolute thresholds from Altman's original manufacturing sample.

What does a negative Z-Score mean?

A negative Z-Score indicates that the weighted sum of the five financial ratios is below zero. This typically occurs when a company has significant negative retained earnings, negative operating income (EBIT), or both. It represents the deepest level of financial distress in the model and suggests the company may be technically insolvent.

How is working capital calculated for this model?

Working capital is simply current assets minus current liabilities, both taken from the balance sheet. A positive figure means current assets cover near-term obligations; a negative one is a warning sign. This calculator derives working capital automatically from the current assets and current liabilities you enter.

Sources

Written by Sarah Klein, CFP Certified Financial Planner · Chicago, USA

Fifteen years translating mortgage tables and amortization schedules into decisions that actually help real borrowers.

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