In recent decades, people’s living standards have improved significantly, but health awareness is still weak. Poor living habits and eating habits have led to a sharp increase in the number of people with diabetes. The complications caused by diabetes are a serious threat to people’s health. Because awareness rate of diabetes is low, many patients with diabetes fail to detect the disease in time, leading to complications. In this study, by analyzing the characteristics of diabetes, according to the characteristics of small sample size and easy to be missing, the IV value analysis is used for feature selection, and CatBoost, a new type of Boosting algorithm, is used to predict diabetes patients and achieves significant predictive effects.