Bank facilities are the main outputs of the bank, through which the society's liquidity, which is placed in a wandering way at the level of the society, is injected into defined and targeted economic sources. In this regard, one of the major problems faced by decision-makers in banks is prioritizing loan applicants. Therefore, this research was conducted to identify the effective factors in developing a model for measuring customers' credit risk and determining a suitable algorithm for prioritizing bank applicants on a case study in Sepeh Bank. In this research, experts' intuitive and imprecise judgments were considered hesitant fuzzy data, and a simple distance-based algorithm was proposed. The output of the proposed algorithm is a detailed ranking of applicants for bank loans. The presented problem in this research is a decisionmaking one that is done intuitively, and so far, no research has been done to provide a prioritization algorithm in this field.