In this paper an influencing factor system of airborne products is established based on a comprehensive consideration of factors like geography, climate, service situation and maintenance level. SVM regression analysis model and forecasting model of airborne products based on SVM are introduced. Then a life prediction model based on SVM is built according to the failure rate data of an airborne product equipped in some representative conditions. It can predict the service life of the product by finding out the relationship between the failure rate and the influencing factors, accordingly it can make up the localization of outfield data statistical method. A case shown in this paper presents the life forecasting process of before-mentioned method and the result indicates that this method is of some value for practical application.