The complex sentence structure of English is a bottleneck to our practical machi ne translation system. The simplification of English subordinate clauses will gr eatly relieves the burden of parsing and other grammatical or semantic analysis of a complex sentence, thus improves the output quality of the MT system. But th ere have not any satisfactory research achievements reported in this field up t o now as we know. In this paper, author's work on a corpus-based approach to English subordinate clause identification is reported. The approach integrate s rule-base d and statistical methods to get the left and right boundaries of the subordinat e clauses. The Penn Treebank corpus is used as the training standard. The precis ion and recall ratios of subordinate clause identification are tested on both cl osed and open corpora. A result of 92.9% precision and 91.26% recall is obtained for the closed test and the open test result is 80.34% precision and 83.93% rec all. This algorithm has been integrated into our machine translation system. The method can also be applied to processing of any other language.