This thesis intergrates a quantitative objective in optimization model with multiple qualitative objectives in the rule rased systems by the Post-Model Analysis(PMA) approach. This thesis develops methods for automatic generation of judgement functions and the methods for automatic evaluation of a solution in terms of qualitative objectives. A couple of algorithms which generate the marginal rate of substitutions are proposed to support the tradeoffs between goals. Finally Intelligent Post-Model Analysis System (IPMAS) is implemented using the Golden Common LISP on IBM-PC AT. This thesis can be contributed to the integration of the quantitative models with the expert systems.