Student diversity plays a crucial role in fostering inclusive education, which enhances innovation, creativity, and problem-solving. In India, while the student mobility is increasing, disparities across regions and institutions continue to influence students’ decision in choosing an institution. Understanding student’s decision making will enhance equal opportunity for quality education. This study aims to identify the factors affecting interstate student diversity in Indian higher education. Secondary data from a national ranking body were analysed using statistical techniques and supervised machine learning algorithms using tool OriginPro 2024 and MATLAB’s R2024a respectively. Statistical analyses, including Pearson correlation, Spearman correlation, and Kruskal–Wallis tests, were employed to analyse relationships among factors, while machine learning models such as Gaussian Process Regression, Ensemble methods, Support Vector Machines, and Kernel-based approaches were used to assess feature importance. The findings show that the factors of student diversity vary across institution types. In Central Government Funded Institutions (CGFIs), location (23%) and course offerings (9%), while in State Government Funded Institutions (SGFIs), international student proportion (17%), were significant factors. For Self-Financed Institutions (SFIs), institutional rank (13%) and placement opportunities (10%) were key factors. These insights can guide policies and strategies to enhance student diversity and promote inclusive education in alignment with National Education Policy (NEP) 2020 and quality education Sustainable Development Goals (SDG) 4.