In this thesis, we present a novel approach to machine translation using syntactic Pattern Recognition (PR) methods. The purpose of this research is to evaluate the possibility of using syntactic PR techniques in this field. To make use of syntactic PR techniques, we propose a system that performs string-matching to pair English sentence structures to Japanese structures. In order to process the sentence structures of either language as a string, we have created a representation that replaces the tokens of a sentence with their respective Part-of-Speech tags. To perform the string-matching
operation we make use of the OptPR algorithm, a syntactic PR scheme that has been proven to achieve optimal accuracy. Through our experiments, we show that our implementation obtains superior results to that of a standard statistical machine translation system on our data set, with the additional guarantee of generating a known sentence structure.