Data Envelopment Analysis (DEA) has been a very popular method for measuring and benchmarking relative efficiency of peer Decision Making Units (DMUs) with multiple input and outputs. However, some problems have also appeared as the applications of DEA advance. One of inter-related problems that has long been known is the lack of discrimination power. The lack of discriminating power problem occurs when the number of DMUs under evaluation is not large enough compared to the total number of inputs-outputs. In this situation, classical DEA models often yield solutions that identify too many DMUs as efficient. In this study the base of the modeling is technique Data Envelopment Analysis But in order to increase accuracy in assessing banks performance and identify the inefficiency and efficiency units, designing a model that combines data envelopment analysis and Goal Programming and also performance of the banks are measured in this perspective. The results of this study showed the higher ability of the presented model toward the basic models to separate the banking units.