Decarbonizing heavy-duty transport requires a deep understanding of the interplay between energy demand and operational continuity. This study presents an integrated, simulation-based framework to compare the energy intensity and reliability of battery-electric (EV) and diesel internal combustion engine (ICE) haul trucks on a real route in Poland. We develop a route-aware model using physical force balance and high-resolution elevation data to estimate energy consumption and recuperation potential. To evaluate operational continuity, a two-parameter Weibull statistical model and Monte Carlo discrete-event simulations are employed to determine failure probability and fleet availability. Furthermore, a Random Forest predictive sensitivity analysis is implemented to quantify the impact of environmental and mechanical variables on system downtime. Results indicate that under baseline conditions on a loaded downhill route (−5.0% average gradient), the EV achieves a unit energy intensity of approximately 0.43 MJ·t⁻¹·km⁻¹, compared with 1.02 MJ·t⁻¹·km⁻¹ for the ICE configuration. However, EVs exhibit a pronounced thermal sensitivity, with extreme winter temperatures increasing energy demand by 45–70%. Despite this, the conditional reliability simulations—based on theoretical and empirical Mean Time Between Failures (MTBF) inputs (250 h for EV vs. 125 h for ICE)—predict a structural availability advantage for electric drivetrains. The proposed multi-dimensional approach provides a robust modelling framework for optimizing maintenance strategies and fleet sizing in transitionary mining environments.