Bamboo is a viable reinforcement material due to its high strength-to-weight ratio, cost-effectiveness, and eco-friendliness. However, raw bamboo poses challenges such as high water absorption and a weak bond with concrete, which can be mitigated by appropriate coating material. An entropy-based fuzzy TOPSIS (Technique for Order of Preference by Similarity to Ideal Solution) model is developed to evaluate and identify the optimal coating material. The entropy method is employed to calculate criteria weights, while fuzzy-TOPSIS is used to rank alternatives by addressing uncertainties and subjective preferences. The data from existing literature supported the selection of thirteen coating materials, evaluated across four criteria: concrete compressive strength, bamboo tensile strength, embedded length, and pullout load. The results indicate that Sikadur-752, an epoxy resin-based material, ranked highest with a relative closeness of 0.6348, demonstrating its superior performance. Sensitivity analysis confirmed the robustness of the model across varied weight scenarios. The proposed model advances coating material selection for bamboo reinforcement, offering a framework for future research. The findings contribute to bamboo-reinforced concrete construction by enhancing its structural performance and longevity.