Transfer learning can improve the performance of classifier effectively, when the training data are out of date, but the new data are very few. In this paper, we propose a transfer learning algorithm for text classification based on clustering. We describe the main idea and the step of the algorithm. Then have experiment on text corpus of Chinese, and compare the algorithm with transfer-unaware algorithm. The experiments demonstrate that this algorithm significantly outperforms the others.