Calantone, Di Benedetto and Schmidt (1999) presented an Analytic Hierarchy Process (AHP) modeling approach to new product screening. The illustration of this approach is an example of a decision support model that seeks to aid managers in selecting new product ideas to pursue. In this paper we improve upon this initial AHP mode using a fuzzy optimization approach. This use of fuzzy math augments the AHP model by providing the ability to cope with the ambiguity ad vagueness that can be inherent within the judgments underlying the analytic hierarchy process. The addition of a fuzzy structure to the standard AHP model provides a clearer decision framework while greatly enhancing the efficiency of the screening process. An empirical example that illustrates the application and benefits of the "fuzzy" approach is provided.