Abstract: The invention relates to method and system for extracting and classifying manufacturing features from a three-dimensional (3D) model of a product. The method includes generating graph corresponding to product based on 3D model of product. The graph includes nodes corresponding to faces of the product and links corresponding to edges of product. The graph generation includes determining adjacency attribute matrix from the 3D model. The method further includes assigning scores to each of links; determining a cumulative score for each of links; extracting sub-graphs from graph by discarding one or more links from links; extracting node parameters and edge parameters from 3D model of product; determining node feature vector based on node parameters and edge feature vector based on edge parameters; and determining a type of manufacturing feature based on corresponding node feature vector and edge feature vector using a Graph Neural Network (GNN) model.