The article "Building Sustainable Business Models with Predictive Analytics: Case Studies from Various Industries" by Edith Ebele Agu, Njideka Rita Chiekezie, Angela Omozele Abhulimen, and Anwuli Nkemchor Obiki-Osafiele explores the significant role of predictive analytics in fostering sustainability across various industries. Predictive analytics enables businesses to anticipate future trends, identify potential risks, and make data-driven decisions, enhancing operational efficiency, improving customer experiences, and driving growth. The authors present case studies from different sectors, including retail, healthcare, financial services, and manufacturing, to illustrate the practical applications and benefits of predictive analytics. In the retail industry, predictive analytics is used for customer segmentation and targeted marketing, as well as inventory management and demand forecasting, leading to increased revenue, reduced costs, and improved customer satisfaction. In healthcare, it aids in disease prediction and prevention, enabling early detection of health risks and proactive interventions, while also optimizing hospital resource management. Financial services leverage predictive analytics for credit risk assessment, fraud detection, and personalized financial services, enhancing regulatory compliance and customer satisfaction. In manufacturing, predictive analytics is used for predictive maintenance and supply chain optimization, reducing downtime and improving operational efficiency. The article concludes that predictive analytics is a powerful tool for building sustainable business models by enabling organizations to make informed decisions, optimize resources, mitigate risks, and meet evolving customer needs. The integration of predictive analytics across industries fosters sustainability and long-term success.The article "Building Sustainable Business Models with Predictive Analytics: Case Studies from Various Industries" by Edith Ebele Agu, Njideka Rita Chiekezie, Angela Omozele Abhulimen, and Anwuli Nkemchor Obiki-Osafiele explores the significant role of predictive analytics in fostering sustainability across various industries. Predictive analytics enables businesses to anticipate future trends, identify potential risks, and make data-driven decisions, enhancing operational efficiency, improving customer experiences, and driving growth. The authors present case studies from different sectors, including retail, healthcare, financial services, and manufacturing, to illustrate the practical applications and benefits of predictive analytics. In the retail industry, predictive analytics is used for customer segmentation and targeted marketing, as well as inventory management and demand forecasting, leading to increased revenue, reduced costs, and improved customer satisfaction. In healthcare, it aids in disease prediction and prevention, enabling early detection of health risks and proactive interventions, while also optimizing hospital resource management. Financial services leverage predictive analytics for credit risk assessment, fraud detection, and personalized financial services, enhancing regulatory compliance and customer satisfaction. In manufacturing, predictive analytics is used for predictive maintenance and supply chain optimization, reducing downtime and improving operational efficiency. The article concludes that predictive analytics is a powerful tool for building sustainable business models by enabling organizations to make informed decisions, optimize resources, mitigate risks, and meet evolving customer needs. The integration of predictive analytics across industries fosters sustainability and long-term success.