Korean and Chinese belong to different language families and there are very few researches on statistical machine translation between them. The word order of these two languages is quite different. Korean is considered as a morphologically rich language when compared to Chinese. Hence, in translating Korean into Chinese, more linguistic knowledge is required to achieve a better translation result. This paper presents a Korean to Chinese machine translation system by incorporating different linguistic data of Korean into the translation model. A state-of-the-art factored translation model is employed to verify the goodness of the proposed approach, which is efficient not only for the European languages, but also for Korean and Chinese. Experimental results demonstrate the solid evidence that the proposed method is able to achieve a better performance by integrating different types of linguistic information. © 2012 IEEE.