Classification of potential customers is necessary to identify potential customers. Customer of PT. Pegadaian is often late in making loan installment payments and is often past the predetermined due date. This can cause losses to PT. The pawn shop itself. In this study, data mining with the C5.0 method will be used to analyze potential customers based on installment payment patterns by selecting attributes that will be processed using information gain. The attribute with the highest information gain value will be chosen as the parent of the next node. Customer data will be analyzed to get a decision. It can be proven that manual calculations are the same as calculations in the application. The results obtained are a decision tree.