There are a lot of uncertainty information in natural Language. It is becoming a focus of researches in NLP recently. However, the research on Chinese is still scarce. In this paper, we use SVM, which is a good solution to the high dimension, nonlinear and local small sample, to identify Chinese uncertainty information recognition as a question of classification. We carry experiment on Chinese uncertainty corpus published by Fudan University, which confirms the availability exposed by our paper based on SVM. Compared to the sentence scoring model, our system has better recall rate.