The establishment of a wing structural load model with flight parameters as variables is an important technical basis for flight safety monitoring and aircraft fatigue life estimation. Firstly, the influence of wing fuel quality on its structural load is separated. On the basis of this and in accordance with the correlation between aircraft structural load and flight parameters, and the lowdimensional and the uncorrelated modeling parameters determined through correlation analysis combined with principal component analysis, a model is established by the BP neural network method pretrained by GaussBernoulli restricted Boltzmann machine. Taking the aircrafts transonic pitch maneuver for example, a shear force model of a certain measured load profile of the wing is established. The model verification results show that the pretraining can effectively reduce the initial error of model, and improve the modeling efficiency and accuracy.