The invention relates to a disease image identification method suitable for multi-size picture information, and overcomes the defects of low identification rate and poor robustness due to that the resolutions and sizes of disease images are different as compared with the prior art. The method of the invention includes the steps of collecting and pre-processing training images; constructing and training an MCNN network model; collecting and pre-processing images under test, shooting disease images to be identified using an acquisition device, and performing histogram equalization of the disease images under test to obtain a test sample; and inputting the test sample into the trained MCNN network model for automatic identification of the disease images. The method of the invention can directly extract features of the images with different resolutions and sizes, without unifying the size of the images before the identification, and perform classification prediction.