To make better use of the feature information obtained from all convolution layers in a Convolutional neural network (CNN), a residual life prediction model of lithium batteries based on multi-scale CNN with jump connection was proposed. The model takes the health factor of the battery as input, uses the multi-scale CNN model based on jump connection, simultaneously extracts the local feature information and global feature information of different scales of the health factor of the lithium-ion battery, and fuses all the local feature information and global feature information through the information fusion module, and finally outputs the predicted value of the remaining life. The experimental results show that the proposed method can predict the remaining battery life more accurately than the traditional method.