Several techniques and methods have been proposed in the past for the study of financial classification problems, including statistical analysis techniques, mathematical programming, multicriteria decision aid and artificial intelligence. The application of these method^ in real world problems, where the decisions have to be taken in real time, calls upoip a powerful and efficient tool for supporting practitioners financial analysts in applying these techniques. This paper presents the FINCLAS (FINancial CLASsification) decin sion support system for financial classification problems. The classification is achieved through the use of the UTADIS (UTilites Additives DIScriminantes) multicriteria decih sion aid method. The main parts of the FINCLAS system and the UTADIS method are discussed, and an application of the system is presented