Aiming at the difficulties caused by little history consumption data of new aircraft spare parts on spare parts predication, put forward the LS-SVM regression algorithm to realize the new aircraft spare parts demand prediction. Introduce the LS-SVM basic principle, establish the new aircraft demand predication model, select kernel function, use LS-SVM to learn the training sample, and train its network structure parameter. Ascertain the optimal parameter by cross-validation and grid-search. Use trained LS-SVM to predict the new aircraft spare part demand, and carry out example simulation. The results proved the excellent effectiveness of LS-SVM in new aircraft spare parts demand predication.