This study addresses this critical knowledge gap through the development of an integrated computational–statistical framework combining finite element analysis (FEA) and quantitative performance metrics to systematically evaluate alumina–UHMWPE and alumina–PEEK bearing couples. Building upon recent clinical wear analyses by Pierce et al.  and fundamental tribological studies by Smith and Jones  and Khan et al, our study introduces three key innovations: (1) the implementation of dynamic gait cycle loading to simulate physiological wear patterns, (2) the development of the Hip Corrosion Index (HCI) as a novel multi-parameter wear assessment metric, and (3) a comparative statistical analysis of wear distribution characteristics between material pairs.