The permanent magnet linear force motor is one of the important components of the direct drive servo valve. Its driving force can cut the metal fragments entering the valve port to prevent the valve port from being blocked by them. Therefore, the accurate prediction of the driving force has extremely important research significance for designing the permanent magnet linear force motor. Firstly, a finite element simulation model of the permanent magnet linear force motor is established with ANSOFT, getting the driving force under the zero position and its limiting current. Secondly, the key structural parameters and their value ranges of the linear force motor are determined according to the optimization goal and constraint conditions. Then, the Latin hypercube algorithm based on the maximum and minimum distance criterion is used to sample data in a muti-dimensional space. Finally, a deep neural network model with a conversion layer is proposed. The conversion layer extracts 100 parameters from motor model, so that deep neural network can combine new high-dimensional features from more features and improve its prediction accuracy. The prediction model of permanent magnet linear force motor driving force used by actuator with PReLU and SmoothL1Loss is established. The comparison with traditional prediction models of both Kriging and RBF proves the effectiveness and accuracy of the new model.