In this study, we propose a fast topology optimization method based on a deep neural network (DNN) that predicts the currentdependent motor torque characteristics using its cross-sectional image. The trained DNN is shown to provide the current condition that provides the maximum torque under the assumed motor control method. The proposed method helps perform topology optimization with a reduced number of field computations while maintaining a high search capability.