Accelerated degradation testing is widely accepted in competitive industries. As there is no longer the need to test till failures, there are tremendous cost and time benefits on fully capitalizing on such a testing regime. Consequently, this research has aimed for better understanding of the relationship between design and degradation using the degradation data. Artificial neural network is widely used for complex problems in the literature. This book proposes and demonstrates the neural network modelling methodology into capturing the non parametric relationship between design and degradation, specific to the particular problem domain. In particular, two models of different practical significance are developed and compiled as Windows executables for predicting material performances.