The banana shelf-life prediction is very crucial in banana supply chains. The high accuracy of banana shelf-life prediction not only can reduce the banana waste but also can improve profitability and customer satisfaction. By precisely predicting the banana shelf-life, farmers, retailers and consumers in the banana supply chain can make informed decisions about the storage, transportation and consumption of bananas. Accurate shelf-life prediction can optimize inventory management, reduce spoilage-related losses, and enhance profitability across the banana supply chain. This proposed research aims to develop new models and algorithms to accurately predict banana shelf-life, based on image and spectral data, in addition to the shelf-life historical data of bananas.