We have designed a campus placement prediction system aimed at assessing a student’s likelihood of securing employment through campus recruitment. This predictive model incorporates multiple parameters to gauge a student’s skill level. Some of these parameters are drawn from the college’s records, including academic performance, CGPA, attendance, and more, while others are derived from assessments conducted within the placement management system. By amalgamating these data points, our model can provide accurate predictions regarding a student’s potential placement in a company. Furthermore, we leverage data from previous group of students to train our model, employing educational data mining techniques to access authentic historical data from our college’s alumni. This approach enhances the efficacy of our machine learning model when making predictions specific to our institution.