The paper introduces the ensemble learning prediction method and dilates on the application of ensemble learning in blood glucose prediction. Based on individual routine physical examination data, it predicts blood glucose through the ensemble learning method that is combined with linear regression, gradient boosted decision tree, random forest and other models. The experimental results indicate that the method boasts higher prediction precision for blood glucose and is able to identify individuals with abnormal blood glucose more accurately.