When the educational environment is in its constant transformation, it is crucial to bring such values as sustainability and innovation in business development to help organizations thrive in the future. This research aims at working out an appropriate business model to support sustainable business models for educational systems with the help of industry-specific predictive models and machine learning (ML). Our method provides a foundation to use data as a means to make better decisions, allocate resources as to provide a higher quality of the educational environment that is more adaptable and sustainable. The use of regression analysis, clustering, and classification in educational institutions helps to draw conclusions and forecasts for action in the future on the basis of using fundamentally effective models in finance. The study also focuses on the contribution of using predictive analytics for the promotion of innovation, student engagement, and learning environment. The present work registered three promising avenues for the application of machine learning models in educational business settings and identified how these changes might help transform linear, resource-intensive business models into circular, sustainable and highly effective models for the success of educational organizations.