Аннотация:This paper is devoted to developing the models of losing bank licenses by Russian banks. The factors of the models are drawn from banks' financial statements and macroeconomic reports. The algorithms proposed are capable to estimate both the probability and the exact time of license revocation. In order to do so multiple choice problem is formulated with the target variable represented the probabilities of revocation within a certain time period after the forecast date. The modeling was conducted using logistic regression model, ensemble of decision trees, gradient boosting and artificial neural network. The results of this study have useful implications both in government organizations and in private companies. The regulators can adjust manageable macroeconomic indicators to control the intensity of bank licenses revocation. Companies can use estimated probabilities in solving funds distribution problems.