The invention discloses a bone age evaluation method based on a convolutional neural network and a multiple attention mechanism. The method comprises the following steps: in a training stage, taking ametacarpal bone image as the input of a backbone network, obtaining a feature map F through a feature extractor, and obtaining a bone age regression value; taking the input of a multi-attention module as a feature map F, obtaining M sub-attention maps through compression operation and attention map splitting operation, conducting point multiplication of each sub-attention map with the feature mapF, and then obtaining a corresponding bone age regression value; combining a backbone network with the bone age regression value obtained by the multiple attention module, and training a neural network by adopting a multi-task learning strategy; and in a test stage: inputting a to-be-tested metacarpal bone image into the trained neural network, and obtaining a bone age evaluation value through the backbone network. The model can be trained end to end; meanwhile, an attention distribution diagram can be automatically generated, and better generalization is achieved; and in addition, based on the 2D convolutional neural network, the speed is high, the precision is high, and an average evaluation error is within 4.1 months.