A stub axle is a part of a vehicle constant-velocity system that transfers engine power from the transaxle to the wheels. The stub axle is subjected to fatigue failures due to cyclic loads arising from various driving conditions. The aim of this paper was to introduce a probabilistic framework for fatigue life reliability analysis that addresses uncertainties that appear in the mechanical properties. Service loads in terms of response-time history signal of a Belgian pave were replicated on a multi-axial spindle-coupled road simulator. The stress-life method was used to estimate the fatigue life of the component. A fatigue life probabilistic model of a stub axle was developed using Monte Carlo simulation where the stress range intercept and slope of the fatigue life curve were selected as random variables. Applying the goodness-of-fit analysis, lognormal was found to be the most suitable distribution for the fatigue life estimates. The fatigue life of the stub axle was found to have the highest reliability between 8000 - 9000 cycles. Because of uncertainties associated with the size effect and machining and manufacturing conditions, the method described in this paper can be effectively applied to determine the probability of failure for mass-produced parts.