 Colorectal cancer is one of the most common types of cancer in the world and it is often difficult to detect at an early stage. Artificial intelligence, AI, specifically machine learning, ML, and deep learning, DL, techniques, have been used to improve the accuracy of diagnosing colorectal cancer. This paper reviews the current literature on AI-based ML and DL techniques applied to the modeling of colorectal cancer. The papers were categorized according to their aim, method, and data samples. The authors also discussed the challenges and opportunities of using these techniques to predict colorectal cancer. This article was authored by Davia Alboanine, Raisin Alcani, Chica Alcatani, and others.