The article discusses approaches to risk management models based on modern information approaches. The described approach to the formation of assumptions arises with the provision of ubiquitous operation of railway transport based on the analysis of events that were not previously widely disseminated due to the occurrence of negative consequences. One of the promising methods for predicting risks is a machine study with the formation of a region of probabilistic results. The use of machine research and application is based on its combination of artificial intelligence, mathematical statistics, numerical methods, probability theory, graph theory. A necessary dimension of machine learning is working with a large amount of data, including data that was not previously represented in statistics. A scheme for working with data on all African realities, strategic risk management is described. The result of using models is the creation of technologies that reduce infrastructure investments, reduce the risk of risks when using transport processes, by taking into account the effects and predicting risks. The trend of “fine dynamics” repeats the processes and, as a result, they probably get a positive effect on the transfer process.