Its goal is to develop college-level forecasting automation, predict the chances of students being placed in information technology companies, and help screen candidates before the hiring process begins. lt involves using machine learning algorithms as a basic model to classify students into appropriate groups, so the results will help them improve their skills and other ways of thinking. The same results are also compared with the results obtained from other models such as logistic regression, random forest, and SVM to obtain the optimal and so on. Placements are considered to be very important for each and every college. The main objective of this model is to predict whether the student gets placed or not in campus recruitment. A high placement rate is a key entity for any educational institution. Hence such a system has a significant place in the educational system of any learning institution.