Multi-objective transportation problems (MOTPs) play a crucial role in optimizing logistics, supply chains, and resource allocation, where multiple conflicting objectives must be balanced. The Fermatean fuzzy programming approach offers an advanced decision-making framework to handle uncertainty and imprecision more effectively than traditional fuzzy methods. By leveraging Fermatean fuzzy sets, which provide higher flexibility in capturing vagueness and hesitancy, this approach enhances the accuracy of transportation models, leading to more realistic and efficient solutions. Researchers and practitioners can apply this method to real-world transportation scenarios, optimizing cost, time, and environmental impact while ensuring robust decision-making in uncertain environments.