Cardiac MRI plays an important role in defining cardiac anatomy and function in children with heart disease. Prescription of diagnostic planes in cardiac MRI requires specialized training, limiting availability. Machine-learning based prescription has the potential to allow rapid, consistent acquisition of these planes independent of operator, but performance in congenital heart disease is unknown. This study evaluates the utility of such a system which demonstrates performance in children with mild to moderate heart disease similar to healthy adult volunteers. As expected, the system does not generate acceptable results in severe intracardiac anomalies.