Statistical machine translation has made great progress in recent years, and Tibetan-Chinese machine translation has many needs. A phrase-based translation model is suitable for machine translation between Tibetan and Chinese, which have similar morphological changes. This paper studies the key technologies of phrase-based Tibetan-Chinese statistical machine translation, including phrase-translation models and reordering models, and proposes a phrase-based Tibetan-Chinese statistical machine translation prototype system. The method proposed in this paper has better accuracy than Moses, the current mainstream model, in the CWMT 2013 development set, and shows great performance improvement.