A line loss rate evaluation method based on Stacking ensemble learning for transformer district with DG was proposed in this paper. Firstly, data of transformer districts with DG were extracted from specific systems and processed by several algorithms to establish the indicators. Then, considering the difference of algorithms, linear regression, random forest and GBDT were involved in base-learner layer. The model based on multi-algorithm combination of Stacking ensemble learning was built. Finally, accuracy and effectiveness of the proposed method is confirmed based on the data of transformer districts with DG. The results demonstrate that the proposed method has better evaluation accuracy and higher generalization compared with the methods of random forest and GDBT.