The VIKOR method depends on a compromise programming technique-derived aggregating function that symbolizes "closeness to the ideal. This approach can be useful when a decision maker is unable or unsure of how to describe their choice at the beginning of system design. Furthermore, due to the hesitant fuzzy set's effectiveness and strength in capturing ambiguity and uncertainty, it has come under increasing scrutiny. The criteria weight average VIKOR method (CWA-VIKOR) is expanded in this work to account for uncertain fuzzy situations, and criteria weight average (CWA) introduced a new idea weight, avW , in place of v and find out central compromise solution. We suggest a CWA-VIKOR method based on these novel techniques, and a real-world example is given to demonstrate how well our method works when dealing with multicriteria decision-making issues involving criteria weight average and hesitant fuzzy preference data.