With the rapid development of distribution network, a large number of automation equipment are continuously connected to and used in it, which brings great challenges to the reliable operation of distribution network. In this paper, two kinds of machine learning algorithms are proposed to predict the reliability of distribution network according to the dynamic law and reliability index characteristics of distribution network. Through data transformation of distribution network data, the prediction interval is changed from [0,1] to [0,+∞), and the transformed data are input to the predict model again. The results of distribution network example validation show that the prediction effect of machine learning is improved obviously after data transformation, and the artificial neural network optimized by dropout technology has the best prediction performance. The model presented in this paper can accurately predict the reliability of distribution network and provide reference for construction investment and optimal operation of distribution network.