Classification of the document image is an essential process in digital libraries, office automation, and various image analysis application. There is considerable diversity in classifying the document either in the problem that needs to be solved using the training data to build a class model, classification approach, and document feature. This thesis will address text document image classification for a case study at Umm Al-Qura University in Saudi. We will highlight the importance of the classifier's design, the proper feature and the feature representation, the best classifier model, and the learning mechanism