Abstract: The traditional method of Litchi yield estimation is manual counting method, which has many problems such as heavy labor, low efficiency and high error. In this paper, a neural network model for Litchi object detection based on YOLOv3 algorithm is built by using artificial intelligence techniques such as computer vision and depth learning,Then predict the number of fruits in the picture and save the results, a MLP neural network model was built, and the number of detected fruits was taken as the input of the network, and the output of the whole tree was inferred. In addition, in order to improve the accuracy of the results, we use binocular vision to obtain the information of measuring position and distance depth of Litchi tree, and use edge detection to get the outline of the tree, finally, the width and height of Litchi tree are obtained, and the results are input into MLP neural network as variables, through edge calculation, image reasoning and recognition calculation, Litchi yield estimation is realized, which can change the traditional artificial litchi yield estimation method, improve the efficiency and lay a foundation for the accurate management of Litchi orchards.