 Arabic text is often written in cursive, making it difficult to recognize by traditional optical character recognition, OCR, methods. We developed three convolutional neural network, CNN, models to improve character recognition accuracy on the Hija dataset. Models C achieved the highest accuracy of 99.3%, demonstrating its potential for use in OCR applications. This article was authored by Mohamed Widadj Brail and Mehmet M. Tenekisi.