The development of artificial intelligence and machine learning provided a new idea for the evaluation of line loss rate of transformer district with DG. A line loss rate evaluation method based on Stacking ensemble learning for transformer district with DG was proposed in this paper. Data of transformer districts with DG was extracted from specific systems and the outliers in the data were processed by means of mutual information to establish the electrical characteristic indicator system, considering the difference between traditional machine learning and different ideas of ensemble learning algorithms, integrated linear model and nonlinear model, linear regression, random forest and GBDT were involved in base-learner layer, and the model based on multi-algorithm combination of Stacking ensemble learning was built, accuracy and effectiveness of the proposed method was confirmed based on the data of transformer districts with DG.