Optimizing systems based on decision-making criteria across multiple sets requires selecting different stages to achieve the best efficiency for the analyst's objective. Therefore, advantages and disadvantages must be considered simultaneously to choose the most effective method. The Hurwicz criterion is an approach that combines pessimistic and optimistic criteria to achieve optimal efficiency. This method allows for solving more complex problems in two or multiple stages. In the standardized combined approach within a two-stage Data Envelopment Analysis (DEA) network, the outputs of the first stage are selected as the inputs of the intermediate stage, ultimately determining the Most Productive Scale Size (MPSS). By applying the Hurwicz method in both optimistic and pessimistic scenarios, the best Decision-Making Units(DMUs) are selected for analysis.