Predictive analytics is a powerful tool for building sustainable business models across various industries. This review explores case studies in retail, healthcare, financial services, and manufacturing to demonstrate how predictive analytics enhances decision-making, operational efficiency, and sustainability. In retail, predictive analytics is used for customer segmentation and targeted marketing, enabling personalized marketing and improved inventory management through demand forecasting. In healthcare, it aids in disease prediction and prevention, optimizing hospital resource management, and improving patient outcomes. Financial services leverage predictive analytics for credit risk assessment, fraud detection, and personalized financial services, enhancing risk management and customer satisfaction. In manufacturing, predictive analytics is applied for predictive maintenance and supply chain optimization, reducing downtime and improving operational efficiency. The integration of predictive analytics allows businesses to anticipate future trends, identify risks, and make data-driven decisions. By analyzing historical data and applying advanced statistical algorithms, organizations can optimize resource allocation, reduce waste, and enhance operational efficiency. These case studies highlight the transformative impact of predictive analytics in building sustainable business models and driving long-term success. Predictive analytics is essential for sustainable growth, enabling businesses to meet evolving customer needs, mitigate risks, and achieve competitive advantage. As industries continue to evolve, the role of predictive analytics in business strategies will become increasingly critical, driving innovation, resilience, and sustainability.Predictive analytics is a powerful tool for building sustainable business models across various industries. This review explores case studies in retail, healthcare, financial services, and manufacturing to demonstrate how predictive analytics enhances decision-making, operational efficiency, and sustainability. In retail, predictive analytics is used for customer segmentation and targeted marketing, enabling personalized marketing and improved inventory management through demand forecasting. In healthcare, it aids in disease prediction and prevention, optimizing hospital resource management, and improving patient outcomes. Financial services leverage predictive analytics for credit risk assessment, fraud detection, and personalized financial services, enhancing risk management and customer satisfaction. In manufacturing, predictive analytics is applied for predictive maintenance and supply chain optimization, reducing downtime and improving operational efficiency. The integration of predictive analytics allows businesses to anticipate future trends, identify risks, and make data-driven decisions. By analyzing historical data and applying advanced statistical algorithms, organizations can optimize resource allocation, reduce waste, and enhance operational efficiency. These case studies highlight the transformative impact of predictive analytics in building sustainable business models and driving long-term success. Predictive analytics is essential for sustainable growth, enabling businesses to meet evolving customer needs, mitigate risks, and achieve competitive advantage. As industries continue to evolve, the role of predictive analytics in business strategies will become increasingly critical, driving innovation, resilience, and sustainability.