In this paper, the optimization mechanism of loading path in hydroforming process is researched. Firstly, the geometric model of an X-shaped tube is established by using 3D drawing software UG; the DYNAFORM software is used to simulate the forming performance of the X tube under different loading paths. The backward displacement is taken as the main factor of the loading path, and the loading path is presented in the form of three factor graphs; it can show the relationship of the main factors of the loading path visually, accurately, and precisely, which are axial feed, internal pressure, and back displacement. Secondly, the orthogonal test method is used to select the optimal loading path, and the back propagation (BP) neural network based on genetic algorithm is used to optimize the loading path of X tubes. Through synthetic consideration of the interrelation of the minimum wall thickness, the maximum wall thickness, the height of branch, and the contact area between branch tube and back punch, the average performance index function is established in the BP neural network control algorithm to optimize the learning efficiency and shorten the calculation time. Finally, verified by experiment, the optimization method of loading path for X tube hydroforming process could control the precision error of results between the simulation and the experiment within 5%, and has high accuracy and good feasibility.