The present study was conducted with the aim of designing a knowledge management implementation model in the Lorestan Railway General Directorate. Given the specific conditions of railway lines in mountainous regions and the importance of traffic and operations management, the utilization and transfer of employees’ tacit knowledge play a crucial role in enhancing the safety and quality of railway services. In terms of purpose, this is an applied study, and methodologically, it follows a descriptive-survey design with a quantitative approach. The statistical population consisted of 220 employees from the Traffic and Operations Department of Lorestan Railway. Data collection was carried out using a researcher-made questionnaire based on the Lee and Hong (2014) model, the reliability of which was confirmed with a Cronbach’s alpha coefficient of 0.91. Data analysis was performed within the CRISP-DM framework utilizing Decision Tree algorithms and Rough Set Theory in Excel, Weka, and Rosetta software environments. The results indicated that the successful implementation of knowledge management is the outcome of the synergy among key components, including knowledge sharing (knowledge system), employee participation in decision-making and support for their creativity and innovation (organizational culture), and information systems (information technology system). A confusion matrix was employed to evaluate the models; the findings revealed that the Rough Sets model achieved an accuracy of 0.925 and a precision of 0.904, while the Decision Tree model yielded a precision of 0.90 and an accuracy of 0.869. The proposed model can serve as an operational framework to facilitate the transfer of experience, reduce operational errors, and enhance safety in the Lorestan Railway.