This comprehensive study delves into the transformative role of machine learning (ML) in various facets of economic analysis and development. By leveraging ML's advanced predictive capabilities, the paper explores its impact on economic forecasting, the analysis of regional economic disparities, sustainable development, and bridging the digital divide. Through empirical analyses and case studies, we demonstrate how ML algorithms enhance the accuracy of GDP forecasts, identify factors contributing to economic inequality, and foster technological innovations that drive productivity and sustainable practices. The paper also addresses the challenges and limitations inherent in the application of ML, such as data quality, model overfitting, and the interpretability of complex algorithms. By offering targeted policy recommendations, this research contributes to the formulation of more effective economic policies and interventions.