The railway transport industry demonstrates significant achievements in various fields of activity through the introduction of predictive analytics. Predictive analytics systems use data from a variety of sources, such as sensor networks, historical data, weather conditions, etc. The article discusses the key areas of application of predictive analytics in railway transport, as well as the advantages, challenges and prospects for further development of this technology in the railway infrastructure.

Keywords: predictive analytics in railway transport, passenger traffic forecasting, freight optimization, maintenance optimization, inventory and supply management, personnel management, financial planning, big data analysis