<p>This research presents a comprehensive analysis of the main factors <br /> affecting the reliability of special self-propelled rolling stock, specifically the ADM <br /> (Avtomotrisa Diesel Mounting) units used in the railway transport system of the <br /> Republic of Uzbekistan. Particular attention is given to key reliability indicators <br /> such as the mean time to failure (MTTF), probability of failure-free operation, <br /> failure rate, and the gamma-percentile life. The study discusses methods for <br /> calculating these indicators and approaches for their quantitative assessment. <br /> The study looked at how different parts of electromechanical equipment, which <br /> work with asynchronous motors and couplings, fail. It was determined that these <br /> failure distributions generally conform to exponential and normal distribution <br /> laws. Mathematical formulas expressing the approximated density of the <br /> reliability distribution are provided, offering more accurate recalibration of <br /> reliability indicators. The analysis is based on technical data from 174 ADM-type <br /> railcars over the period from 2019 to 2023. Diagnostic reports and operational <br /> documents were used as primary sources for evaluating breakdowns and failures. <br /> The study examines the reliability of mechanical, electrical, and hydraulic systems, <br /> identifies the main causes of malfunctions, and assesses their impact on overall <br /> system reliability. The scientific novelty lies in the development of a predictive <br /> model for reliability assessment based on the operational condition parameters <br /> of the railcars and the construction of a regression equation. The obtained <br /> results demonstrate the potential for improving reliability through optimization <br /> of operating modes and enhancement of maintenance systems. The practical <br /> significance of this research is that the proposed methodology allows for effective <br /> evaluation of equipment reliability using statistical data. Moreover, it serves as <br /> a valuable tool for making informed management decisions aimed at extending <br /> service life and improving the operational readiness of rolling stock.</p>