For the problem that the dependent variable has many independent variables and their sampling periods are also different, a predicting method is proposed by using synthetically the data analysis methods of support vector regression (SVR), multivariate regression and principal component analysis, etc. The method can be briefly described as follows: 1. Predicting with the independent variables which have dense sampling periods based on SVR, and then the results are synchronized to have the same sampling period with the dependent variable. 2. Amending the results by using another linear or non-linear method which includes SVR itself, with the rest independent variables which have the same sampling periods with the dependent variable. 3. In order to increase the predictive accuracy, three data processing methods (principal component analysis, standardization and normalization) are integrated. 4. Two approaches, error mean square line and small error probability, are also introduced to evaluating this synthetic method. By using the method, the mathematical relation between the aircraft's failure ratio and its anfractuous factors is first established. The results show that the method is efficient in predicting the aircraft's failure ratio. In the process of quantifying some influencing factors of the aircraft's failure ratio, the Pearson's correlation coefficient method is also adopted.