The article considers approaches and methods of machine learning for forecasting the probability of various types of emergency situations arising during arctic transportation by mixed river-sea vessels based on the input data set, and proposes models for solving the problems of forecasting emergency situations in the northern sea route. The classification of input data for machine learning algorithms was demonstrated, problems in the data and their characteristics were identified, and options for solving these problems were proposed