The present invention relates to a method and a system for predicting the load of a power distribution network. The method comprises the steps of obtaining a unsupervised training sample set, a supervised training sample set and a test sample set according to the time information and on the basis of the historical load influence factor of the power distribution network and the historical load value of a to-be-predicted area; according to the unsupervised training sample set, subjecting a DBN model layer in a pre-established load prediction model to unsupervised training layer by layer, wherein the load prediction model includes a DBN model layer and a linear neural network layer; adopting network parameters obtained through during the unsupervised training step as the network parameter initial values of the load prediction model; according to the supervised training sample set, subjecting the load prediction model to supervised training, and obtaining an optimal load prediction model; testing the test sample set by using the optimal load prediction model so as to obtain a load prediction value of the to-be-predicted area. The present invention can realize the high-precision loadprediction of the intelligent power grid environment under the influence of various factors.