Methods and systems identify frequently-used CAD components and apply machine learning techniques to predict mateable entities and corresponding mate types for those components to automatically add components to a CAD model. An example method includes accessing information regarding CAD model parts and related mate information stored in a computer database, and dividing parts into a plurality of clusters having parts with similar global shape signatures. In response to a new part being added, contextual signatures of entities of the new part are input into a mateability predictor neural network to determine a mateable entity of the new part. Input into a mate-type predictor neural network is (i) a contextual signature of the mateable entity and (ii) a contextual signature of an entity of another part of the CAD model to determine a mate type between the entities. A mate between the new part and the other part is automatically added based on the determined mate type.