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-driven fuzzy TOPSIS (Technique for Order of Preference by Similarity to Ideal Solution) is intended to analyze and determine the optimal coating material. Entropy method is used to compute criteria weights whereas fuzzy-TOPSIS is used to rank alternatives by solving uncertainties and subjective preferences. The data set used was literature-based to make a decision on thirteen coating materials, the properties of which were studied based on four parameters, namely concrete compressive strength, bamboo tensile strength, embedded length and the pullout load. The results show that the epoxy-based resin material Sikadur-752 had the highest relative clossness of 0.6348. To ensure that the model was reliable under different weight scenarios, sensitivity analysis was also carried out. The proposed model advances coating material selection for bamboo reinforcement, offering a framework for future research. This study contributes to the development of bamboo-reinforced concrete construction for improving structural performance and service life.