In view of the fact that the traditional demand forecasting method for spare parts of aircraft materials neglects the acquisition of demand constrained scheduling conditions, which leads to low efficiency and high cost of demand forecasting for spare parts of aircraft materials, a new demand forecasting method for consumable spare parts of aircraft materials based on constrained demand forecasting is proposed and tested. Assuming that the reserve density of a consumable spare parts satisfies Poisson distribution, the timely support probability of the consumable spare parts is calculated. According to the annual turnover of aircraft materials, the total reserves required for different turnover parts are calculated to obtain the total timely guarantee rate. The constrained dispatching condition is given. The constrained dispatching and the minimum cost of demand forecasting are used as the objective function to construct the demand forecasting model of consumable spare parts for aviation materials. The genetic algorithm is used to solve the model and obtain the optimal demand forecasting result. By comparing the method of literature [5] with that of literature [6], it is found that the proposed method has high accuracy, high efficiency and can meet the emergency requirements.