Abstract: The GNRR neural network model with initial forging temperature, final forging temperature, die preheating temperature, forging speed as the input layer, and tensile strength, forming load and wear amount as the output layer was established. Based on this model, the hot forging process of the automobile steering knuckle was optimized. The results show that when the automotive steering knuckle forgings are optimized by using GRNN neural network process parameters, their tensile strength is increased from 774 MPa to 786 MPa, and the forming load and wear volume are reduced from 25.6 MN and 120 μm to 23.5 MN and 115 μm, respectively, the improvement rate of tensile strength is 1.55%, and the reduction rate of forming load and wear amount is 8.2% and 4.2%, respectively. The optimal thermal forging process parameters are the initial forging temperature of 1260℃, the final forging temperature of 1140℃, the die preheating temperature of 230℃, and the forging speed of 48 mm/s.