 This study investigated the use of machine learning techniques to predict the success of science fiction films. Fourteen different algorithms were tested, including the fine, medium, and weighted K&N algorithms. The results showed that the weighted K&N algorithm had the highest accuracy, precision, and recall rates, and also had the fastest execution time. By coupling multiple K&N algorithms targeting specific viewer behaviors, the film industry and its global expansion can benefit from accurate and consistent forecasts. This article was authored by Amjad Al Faham and Tahani Egoban.