A new method to solve Chinese text chunking was introduced as conditional random fields (CRF) model, by which Chinese text chunking transformed into labeling the words with their chunk tags and establishing a model for tagged corpus according to conditional random fields so as to predict the chunk tag of each word. An F1 score of 85.5% is achieved by using the evaluation dataset of Chinese treebank of Beijing university, and obviously better than those of hidden Markov model and maximum entropy Markov model. Experimental results show that conditional random fields model is an effective way on Chinese text chunking and the strict Independence hypothesis and the label bias problem are avoided.