Recognition and rewards consistently motivate students to excel in their academic studies. Simultaneously, students are eager to verify and justify their marks based on their efforts and preparation for examinations. However, due to the pandemic’s devastation and the prolonged effects of COVID-19, many students have been distracted from their studies, showing little enthusiasm for their goals, particularly as they became accustomed to earning marks without sitting for examinations or through online assessments. To address this, the proposed educational performance prediction tool aims to forecast the marks for regular courses based on students’ efforts. By enabling students to anticipate their marks, this tool encourages them to engage with virtual teaching platforms, allowing them to monitor their performance or grades based on their study hours. This not only inspires students to persist in their studies but also strives for excellence. The objective of this article is to introduce a novel tool based on machine learning regression methods for predicting educational performance, designed for easy access and comprehension by end-users.