In this paper, we focus on an Optical Character Recognition (OCR) system for printed text documents in Khmer language by using Zernike Moment. The Zernike Moment method is used as a feature extraction method to solve the recognition problem. We compute the moments from sub-characters to extract their feature vectors. The final recognition result is achieved by employing a classifier based on the Nearest Neighbor method. The method is experimented on 5 documents with font size of 12, 15, and 36 respectively.