Regression analysis is perhaps the most frequently used statistical tools for the analysis of data in practice. The purpose of determining predictor importance is not model selection, but rather uncovering the individual contribution of the predictor relative to each other within a selected model. The purpose of this article is to expand the current research practice by developing a statistical model in the Bayesian framework to assess the relative importance of each predictor in a multiple regression model with a weighted Bradley-Terry model. Results from four sets simulation studies show that the proposed weighted Bradley-Terry model provides the most efficient and reliable measure of the relative importance of predictors.