PLACIFY: AI-Based Placement Prediction and Skill Gap Analysis

The rapid evolution of the job market and the growing emphasis on employability have necessitated advanced tools for

assessing students’ placement readiness and identifying skill gaps. This research proposes “Placify,” an AI-based system

leveraging machine learning techniques for placement prediction and skill gap detection among college students. Motivated by

the limitations of traditional, expert-driven approaches and the scalability offered by AI, Placify employs models such as

Random Forest, XGBoost, and Artificial Neural Networks to analyze academic, demographic, and skill-related features. The

system achieves high predictive performance, with Random Forest models attaining approximately 91% accuracy in placement

prediction tasks. Beyond prediction, Placify integrates skill gap analytics, drawing from contemporary developments in large

language models for prerequisite skill inference to offer actionable insights for learners and institutions. The study underscores

the potential of AI-driven employability analytics in supporting personalized learning and institutional strategy, and discusses

future integration with real-time job market data and automated resume parsing. This work contributes to the growing body of

employability analytics and demonstrates how AI can drive scalable, data-driven educational and career guidance.