The essential method of application of weighted least squares support vector machines (WLS-SVM) to time series forecasting is introduced in detail in this paper, and the general framework for one dimensional time series modeling forecasting is proposed. BIC rule is adopted to select the embedded dimension, and a model performance evaluation method based on statistic is presented. The WLS-SVM model and AR model are set up and used to forecast the status of airplane based on the representative parameters, also the comparison result between the two models is given. The result shows that the WLS-SVM has excellent extended capability because the new type of structural risk minimization principle is adopted, and simultaneously it is of high accuracy and has long forecasting intervals.