In this study, the reliability of turbochargers installed on freight locomotives was investigated using the Weibull distribution. The statistical dataset, comprising 516 records from 132 turbochargers over the period 2016 to 2023, was analyzed. First, after data cleansing, the useful life of the turbochargers was extracted, and then reliability models were developed based on two turbocharger types and service technicians. The results demonstrate that turbochargers from manufacturer D, which operate at lower rotational speeds, have a higher mean life and greater reliability than type A, with the failure rate concentrated in the early-failure phase. To optimize maintenance policies, a life‑cycle model based on Monte Carlo simulation was developed, in which the probability distributions of failure times, repairs, and preventive maintenance (PM) were estimated using real-world data. Then, by varying the decision parameter of the waiting time for turbocharger replacement, the number of turbochargers ready for operation and the downtime duration were analyzed. The results of this model can substantially aid in designing optimal repair and maintenance policies to enhance reliability and reduce costs.