A train control system uses machine learning for implementing handovers between centralized and distributed train control models. A machine learning engine receives training data from a data acquisition hub, receives a centralized train control model from a centralized virtual system modeling engine, and receives an edge-based train control model from an edge-based virtual system modeling engine. The machine learning engine trains a learning system using the training data to enable the machine learning engine to predict when a locomotive of the train will enter a geo-fence where communication between the edge-based computer processing system and the centralized computer processing system will be inhibited.