The cost of transportation is one of the most important expenses for any organization with a supply chain. Over the last few decades, fuzzy decision-making has received a lot of interest in the fields of science, technology, economics, and business, among others. The neutrosophic set concept introduces a new tool for managing uncertainty. The primary aim of this work is to develop a new technique for solving the Pentagonal Neutrosophic Fuzzy Transportation Problem. In particular, we focus on a transportation issue with single-valued pentagonal neutrosophic numbers in which demand, stock, and expenses for transportation are all uncertain. The objective of this study is to reduce the total transportation expenses. For this, first developed a novel ranking technique for transforming single valued pentagonal neutro-sophic figures into crisp quantities. The average deviation technique is then applied to the transportation problem using the Excel solver to find an initial basic feasible solution (IBFS). Furthermore, the modified distribution (MODI) method is employed to find the optimal solution. The recommended strategy is explained using numerical models, and it is compared to the existing approach.