The chapter introduces the growing importance of cross-border e-commerce and the challenges it poses, particularly in managing the global supply chain. It highlights the need for advanced demand forecasting and efficient supply chain management, especially in the context of temperature-sensitive products like food and pharmaceuticals. The research aims to address these issues by developing a Short-Term Demand-based Deep Neural Network and a Cold Supply Chain Optimization method. This approach leverages deep learning techniques to improve the accuracy of sales forecasts, enhancing procurement and inventory optimization. The study also discusses the application of AI and blockchain technologies in logistics and supply chain management, emphasizing the benefits of automated systems and data accuracy. The main contributions of the research include the creation of marketing prediction models using deep neural networks and the use of Bayesian neural networks for future sales forecasting. The paper is structured into sections covering existing cross-border e-commerce and supply chain networks, the working principle of the proposed model, results and comparisons, and conclusions with future scope.The chapter introduces the growing importance of cross-border e-commerce and the challenges it poses, particularly in managing the global supply chain. It highlights the need for advanced demand forecasting and efficient supply chain management, especially in the context of temperature-sensitive products like food and pharmaceuticals. The research aims to address these issues by developing a Short-Term Demand-based Deep Neural Network and a Cold Supply Chain Optimization method. This approach leverages deep learning techniques to improve the accuracy of sales forecasts, enhancing procurement and inventory optimization. The study also discusses the application of AI and blockchain technologies in logistics and supply chain management, emphasizing the benefits of automated systems and data accuracy. The main contributions of the research include the creation of marketing prediction models using deep neural networks and the use of Bayesian neural networks for future sales forecasting. The paper is structured into sections covering existing cross-border e-commerce and supply chain networks, the working principle of the proposed model, results and comparisons, and conclusions with future scope.