The proton exchange membrane fuel cells (PEMFC) are preferred in hydrogen mobility. The performance of PEMFC components may reduce due to the detrimental effects of microcontacts in the internal parts of PEMFC which use metallic foams. Vehicle vibration and bolt clamping stresses are major causes of fretting in PEMFCs. The gas diffusion layer in a PEMFC, which allows the reactants and gases to pass through, is clogged due to the debris generated by fretting. The study examines the failures associated with fretting and their impact on PEMFC power output and service life, considering factors such as contact pressure, relative motion, frequency of oscillation, and the number of cycles. A critical aspect of fretting analysis is the estimation of wear volume, which poses challenges due to the complex nature of fretting damage. Simulated experiments were conducted using in-house developed simulator to assess the debris generation in a single contact. The project also explores the potential of artificial neural networks (ANNs) as an alternative approach for predicting fretting wear volume for the same set of parameters. Time series analysis techniques are also examined to forecast fretting wear by considering patterns and trends in wear progression. The wear volume predicted is then used to predict the contamination in fuel cells and reduction in power generation in fuel cells.