The invention discloses a facial expression recognition method based on a confidence region and multi-feature weighted fusion. The method comprises steps: 1, a face confidence region image and a face region image are acquired, wherein the face confidence region image at least comprises an eye and brow region and a mouth region; 2, the face confidence region image and the face region image are subjected to feature extraction to acquire corresponding initial features; 3, after dimension reduction and data normalization processing are carried out on the initial features, a fusion feature F is formed; 4, the fusion feature F serves as a classification recognition feature to be sent to a classifier for recognition; 5, training set feature data and test set feature data are selected, the training set feature data are inputted to a GRNN neural network for training, and corresponding training parameters are acquired; and 6, based on the training parameters, a density function is adopted to carry out prediction output on the test set feature data to acquire final classification recognition feature data. The method has the advantages of higher recognition efficiency and higher recognition accuracy.