The objective of this paper is to find an appropriate combination of English factors to support English-to-Thai translation task. There are four English factors those are surface, lemma, part-of-speech (POS) and combinatory categorical grammar (CCG). Various combinations of those factors were trained to build the most efficient model for translation. We test the accuracy using the BLEU score. The result shows that the factored model which consists of lemma and CCG produce the highest accuracy at 24.21% (1.05% superior than baseline). In future work, we will extend this work to Thai-to-English translation.