Scholar placement is a crucial aspect of academic institutions, impacting admissions. Institutions enhance placement departments to bolster this process. This paper analyzes historical student data to predict placements, presenting a recommendation system employing Naive Bayes and K Neighbors algorithms to increase efficiency. The system aids in identifying potential students for skill improvement.

• Academic Placement
• Predictive Analytics
• Recommendation System