This study evaluates the reliability of freight locomotive turbochargers using Weibull distribution analysis. We analyzed a dataset comprising 516 operational records from 132 units collected between 2016 and 2023. Following rigorous data cleaning, we determined the characteristic life of the turbochargers and developed reliability models stratified by manufacturer type and maintenance personnel. Our findings indicate that turbochargers from Manufacturer D—which operate at lower rotational speeds—exhibit superior mean time to failure (MTTF) and reliability compared to Type A units, which demonstrate a marked propensity for infant mortality failure. To refine maintenance strategies, we developed a life-cycle model utilizing Monte Carlo simulation, parameterized by empirical probability distributions of failure times, repairs, and preventive maintenance (PM) intervals. By iterating the Maximum Permitted Repair Time (MPRT) parameter, we evaluated the sensitivity of fleet operational availability and downtime. These results provide a robust quantitative framework for designing optimal maintenance policies that maximize fleet availability while minimizing operational costs.