Retail chains have become an integral part of our lives. The growth and development of retail networks depend on numerous factors. On the one hand, competition among retailers drives the improvement of retail chains. On the other hand, customer demand in retail is influenced by various mechanisms such as discounts, sales promotions, bonuses, and other incentives. Additionally, economic changes significantly affect retail performance, including inflation, interest rate hikes, currency exchange rate fluctuations, and overall economic instability. The future of retail lies in adopting an innovative approach. The innovative development of retail chains is grounded in the use of digital technologies that consider consumer habits, environmental and social aspects, market consolidation, and competition in the retail industry. In such a dynamic environment, retail managers must rely on analytical data derived from various sources. It is crucial not only to make timely decisions but also to predict financial performance. This research examines the development trends of three major retailers and substantiates the use of predictive analytics as a tool for forecasting the growth of retail networks. The authors focus on areas such as demand forecasting, price management, logistics optimization, fraud detection, and marketing research.