Predictive Analytics for Sustainable Real Estate: Enhancing Rental Property Evaluation using Machine Learning

This research investigates the integration of predictive analytics and machine learning techniques for evaluating rental properties within a sustainable real estate framework. The study demonstrates how advanced data-driven approaches can enhance decision-making processes for investors, property managers, and tenants while promoting environmental sustainability. By leveraging diverse datasets including property characteristics, environmental features, market trends, and sustainability metrics, machine learning models achieve superior accuracy in rental price prediction compared to traditional valuation methods.