In recent years, with the development of artificial intelligence technology, deep neural network has been widely used in intelligent manufacturing. This paper combines deep neural network with aircraft deformation prediction, proposes a prediction method of aircraft segment deformation based on graph convolution and multi-mode. In the deformation analysis of aircraft segment, the model extracts the features of aircraft structure mode and working condition mode respectively, and fusion at the decision-making level. When extract features from aircraft segment structure data, the aircraft structure data is in point cloud format and has the characteristics of non-Euclidean data, this paper introduce the graph convolution. Based on ModelNet40 and real aircraft segment working condition data, construct aircraft segment deformation dataset deformation dataset including four aircraft segments, and experiments are conducted on this dataset. The experimental results show that the prediction mean square error of this method is 0.188, and get the best prediction in the nose segment of the aircraft, which can effectively predict the deformation of aircraft segments.