In statistics, logistic regression, or logit regression, or logit model is a regression model where the dependent variable (DV) is categorical.

Logistic regression was developed by statistician David Cox in 1958 (although much work was done in the single independent variable case almost two decades earlier). The binary logistic model is used to estimate the probability of a binary response based on one or more predictor (or independent) variables (features). As such it is not a classification method. It could be called a qualitative response/discrete choice model in the terminology of economics.