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This paper explains C4.5 decision tree-based DSS. To help the process of C4.5, entropy-based multi interval discretization model is used for finding cut-off points on a numerical predictor variable. The design includes all the components of DSS, i.e. database, models, knowledge, and dialogue. The DSS consists of three modules namely learning modules, exploration, and applications. Next, the design was implemented in a web-based computer application with training data in csv format as an input. This DSS model is a generic model that can be used on any decision analysis requiring C4.5.