Decision support systems (DSS) have become increasingly important in medical applications, particularly when important decision must be made effectively and reliably. The best way to design a successful DSS is through the participative design, thereafter conceptual simple decision making models with the possibility of automating learning should be considered in the design phase and then implemented by conceptual simple paradigms. In this paper we present a cardiological decision support system, called RO2SE (computeRised prOlapse Syndrome dEtermination, O2 stands for Object Oriented implementation), based on decision tree approach and automatic learning, supporting the process of mitral valve prolapse determination. RO2SE is implemented using Object Oriented visual programming language.