International Journal of Scientific Research and Engineering Development

Campus placement is a critical milestone for students and institutions alike. This paper presents an intelligent platform that leverages Machine Learning (ML) algorithms to predict a student's placement likelihood and analyses career outcomes based on academic performance, skill sets, and extra-curricular data. The system employs Random Forest and Logistic Regression models trained on multi-factor datasets including CGPA, 10th and 12th percentages, internship experience, technical and communication skills, and aptitude test scores. The platform provides personalised dashboards with skill gap analysis and career recommendations, enables placement cells to conduct data-driven recruitment drives, and supports batch prediction and exportable reports. This work addresses the critical gap in campus placement infrastructure where institutions rely on manual, CGPA-only evaluation — replacing guesswork with evidence-based prediction.

Mr.R.Ramakrishnan, S.Gokulakrishnan,"Campus Placement Prediction and Career Outcome Analytics Platform" International Journal of Scientific Research and Engineering Development, V9(3): Page(1429-1434) May-June 2026. ISSN: 2581-7175. www.ijsred.com. Published by Scientific and Academic Research Publishing.