Abstract: A method for predicting a size range of a lost circulation channel based on deep learning (DL) is provided. The method includes the following steps: S1: acquiring data of the lost circulation channel, and establishing a prediction dataset of the size range of the lost circulation channel; S2: preprocessing the prediction dataset of the size range of the lost circulation channel, and determining the size range of the lost circulation channel; S3: establishing a prediction model for the size range of the lost circulation channel; and S4: optimizing the prediction model for the size range of the lost circulation channel, and predicting the size range of the lost circulation channel. The method overcomes the shortcomings of conventional methods, for example, the prediction value of the size of the downhole lost circulation channel is single, inaccurate and not real-time.