In today’s educational landscape, students often face challenges in career development due to insufficient self-construction and decisive decision-making skills. Existing models employ machine learning for student-educational-factors-based analysis but typically involve superficial depth lacking the necessary robustness, particularly when answering multi-step queries pertaining to long periods of time. This research study proposes a personal career advisory system based on the interactive games, where students’ skills and interests will be assessed, and through it, students’ decisions will mirror their preferences and abilities, where the system can dynamically predict some suitable career paths. To manage any deviation in the optimal path of a career, we provide corrective feedback from the system to guide the student back on the track using Explainable AI. In addition, the platform has a Simulation RPG framework that provides a realistic simulation feature to allow students to experience the nuances of their potential career field before fully committing. This immersive approach provides customized career advice and practical insight into prospective careers, empowering students to make informed decisions about their educational and career trajectories.