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Strengthening of masonry members using externally bonded (EB) fiber-reinforced polymer (FRP) composites has become a famous structural strengthening method over the past decade due to the popular advantages of FRP composites, including their high strength-to-weight ratio and excellent corrosion resistance. In this study, gene expression programming (GEP), as a novel tool, has been used to predict the debonding strength of retrofitted masonry members. The predictions of the new debonding resistance model, as well as several other models, are evaluated by comparing their estimates with experimental results of a large test database. The results indicate that the new model has the best efficiency among the models examined and represents an improvement to other models. The root mean square errors (RMSE) of the best empirical Kashyap model in training and test data were, respectively, reduced by 51.7% and 41.3% using the GEP model in estimating debonding strength.