The most crucial factor that survives enterprises under stiff competition is the success of new product development project; thus, the new product development project selection has become the vital concerns of R&D managers. The initial stage of the project is filled with uncertainties and complexities, which significantly deteriorate the success of product development and product launch. Previous researches focus on helping enterprises determine a set of good product ideas; however, when proceeding to the product development stage after the fuzzy front end, a best product idea should be selected to form a new product development project to create anticipated profits and develop competitive advantage. Therefore, this study proposes a potential project selection model, which combines optimal aggregation method and effective fuzzy weighted average to assist decision maker to achieve the best consistency of fuzzy judgments, and generates a single synergistic index project fuzzy synthetic rating that considers both risk and performance. The project fuzzy synthetic rating index is then used to help make the project Go-Kill decision, and the remaining survival projects are next prioritized to filter the best project. This model can efficiently assist R&D managers in dealing with both uncertainties and complexities when making new product development project screening decision and can reduce decision bias and produce new product development project with the highest possibility of generating expected profit.