The invention provides a method and system for predicting the sintered SmCo magnetic performance based on a neural network and relates to the technical field of magnetic materials and machine learningapplication. According to the components and technological parameters of the sintered SmCo permanent magnet, the magnetic parameters of the sintered SmCo permanent magnet are accurately predicted, the components comprise the weight percentage contents of Zr, Cu and Sm elements, and the technological parameters mainly comprise the solid solution temperature, the solid solution time, the sinteringtemperature, the secondary sintering temperature, the secondary sintering time, the pre-aging temperature, the pre-aging time and the aging temperature. And the four core performance parameters of theresidual magnetism, the coercive force, the maximum magnetic energy product and the squareness of the magnet are predicted by integrating the components and the technological parameters. On the basisof the principles of feedforward transmission and back propagation, an artificial neural network model is constructed; a sampling method of an activation function and a training set is optimized, sothat the model achieves ideal fitting and prediction effects.