In recent years, the application of artificial intelligence technology in rectal cancer radiotherapy has become increasingly significant. By constructing models from patient clinical information, accurate prediction of dose distribution, treatment effect, and toxic side effects of rectal cancer can be achieved. This allows optimizing the radiotherapy plan, ensuring the dose is focused on the tumor target area while reducing the radiation damage to the bladder, rectum, and other surrounding tissues. Thus, it can achieve precision and personalization in radiotherapy. In this review, the construction method of artificial intelligence predictive models was described, and the value of different predictive factors to the model was systematically analyzed, including patient clinical data, radiomics, and dosimetry. Moreover, the application and limitations of artificial intelligence predictive models in radiotherapy were summarized. This information can serve as a reference for the clinical application of artificial intelligence predictive models in rectal cancer radiotherapy.