Logistic Regression Calculator

Calculate the predicted probability, odds, and odds ratio from logistic regression coefficients. Visualize the S-shaped probability curve.

Inputs

Intercept (β₀)

Coefficient (β₁)

Predictor Value (x)

Tab to move between fields

Results

Predicted Probability

0.73

Odds Ratio (per unit x)

1.65

Odds2.72

Log-Odds (Logit)1

Predicted Class (0 or 1)1

Marginal Effect at x0.1

How to Use This Calculator

Enter Intercept (β₀), Coefficient (β₁), and Predictor Value (x).
Review Predicted Probability and Odds Ratio (per unit x).
Use Odds and Log-Odds (Logit) to inform your decision.
Use the chart to visualize the results and explore different scenarios by adjusting inputs.

How the result changes with Coefficient (β₁)

Coefficient (β₁)	Predicted Probability	Odds Ratio (per unit x)
-8	0	0
-3	0	0.05
3	1	20.09
8	1	2,980.96

What each input means

Intercept (β₀): The intercept coefficient of the logistic regression model.
Coefficient (β₁): The slope coefficient for the predictor variable x.
Predictor Value (x): The value of the independent variable for which to predict probability.

How this is calculated

Worked example, using the default values

Identify Input Parameters
Intercept (β₀) = -3, Coefficient (β₁) = 0.5, Predictor Value (x) = 8 = 3 input(s) provided
Calculate Predicted Probability
Predicted Probability
0.7311 = 0.7311
Calculate Odds Ratio
Odds Ratio = Math
1.6487 = 1.6487
Calculate Odds
Odds = Math
2.7183 = 2.7183
Calculate Log-Odds
Log-Odds
1 = 1

Engine last updated July 21, 2026. Checked against 2 independently-derived tests — how we verify calculators.

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