There is a trend in the automotive industry to reduce the number of physical prototypes and to rely more on Computer Aided Engineering (CAE) for sizing and final design of vehicle structures. The traditional deterministic approach does not necessarily clarify the degree of variability and conservatism. With small variability in influence parameters and a design factor for final design, the approach may be over conservative resulting in weight and cost penalty. On the other hand, with large variability and the same design factor, the deterministic approach may not satisfy durability requirements. It is important to identify the variability of all factors including road loads and sensitivities of the control parameters, and to minimize their effects on durability so that fatigue life distribution meets the durability requirements. Low cycle fatigue approach is used for all calculations for reliability oriented design that is based on probabilistic rather than deterministic descriptions of design variables. The objective of this study is to develop a method to understand the fatigue influence factors and the effects of their variabilities on a typical automotive shock tower reliability. The study includes determination of fatigue influence factors, Response Surface Model (RSM), and finally the probability/reliability plots for the shock tower model. The CAE process consists of generating systematic computer experimentation matrices using Design Of Experiments (DOE) with (1) Latin Hypercube (LH) sampling and (2) Orthogonal Arrays (OA) within the design ranges. Next, critical finite elements are determined and fatigue life is calculated for each design configuration in the experimentation matrices for the shock tower structure. Fatigue influence factors and Response Surface Models (RSMs) are determined using non-linear regression analysis for Latin Hypercube (LH) sampling and linear regression analysis for Orthogonal Array (OA) method and the results are compared. Finally, a Monte Carlo Simulation method is used to obtain probability/reliability estimation. Based upon the results, fatigue life distributions can be aligned to match the durability requirements by providing appropriate design direction. The method can be extended to various other critical structures and such plots can be generated and used for future design of similar structures.