This paper presents a neural network-based prototype Decision Support System (DSS) developed to support decision-makers when forming manufacturing cells by applying group technology. The DSS was designed to support decision-making problems involving either the complete reconfiguration of manufacturing cells or the placement of specific machines in response to changing manufacturing conditions. By incorporating what-if capability, which is an essential requirement of a DSS, the system was implemented to support decision-makers more efficiently and effectively. Various data necessary for manufacturing cell formation are stored and managed in a database, and as the problem-solving technique, a modified version of the Carpenter-Grossberg Neural Network (CGNN), which has been recognized for producing good results despite its simplicity, is employed. The conceptual framework of the DSS presented in this study is expected to not only accommodate many other manufacturing cell formation models to support decision-makers' decisions but also to be readily applicable to problems in other domains.