The match factor (MF) is a simple criterion used to measure truck-shovel compatibility and is the function of the number of trucks and shovels, truck cycle time and shovel loading time. Current formula of MF ignores random nature of shovel and truck availabilities, and truck cycle and shovel loading time. Furthermore, MF dynamically fluctuates over the time due to variation in road conditions, climate, operator habits and possibilities of the equipment failures. The changing MF value should be monitored and analyzed carefully. Otherwise, it can cause opportunity cost due to the truck queues or shovel idle time. In this research, the risk associated with the uncertainties in MF is assessed with a novel approach in which the probable realizations of number of available equipment are generated by Markov Chain Monte Carlo Simulation (MCMS) and the probable realizations of the shovel loading time and truck cycle time are generated by Ordinary Monte Carlo Simulation (OMCS). Hence, the fluctuations in MF over time is quantified to assist maintenance management and production planning in mining operations by incorporating the reliability of the equipment in the MF equation. To see the performance the proposed approach, a case study was carried out on a mining fleet. The results showed that the proposed technique is a useful tool to quantify the risk associated with deviations from planned production targets.