Soft computing tools in the form of combination of multiple nonlinear regression and M5′ model tree were used for estimation of overtopping rate at the vertical coastal structures. For reliable and precise estimation of overtopping rate, the experimental data available in the database CLASH were used. The dimensionless overtopping rate was estimated in terms of conventional dimensionless parameters including the relative crest freeboard R_c/H_s, seabed slope tanθ, deep water wave steepness S_(om), surf similarity ξ_(om) and local relative water depth h_t/H_s. The accuracy of the new model was compared with other existing models and also evaluated with some field measurements. The results indicated that the model presented in this paper is more accurate than other existing models. With statistical parameters, it is shown that the accuracy of predictions in the new model is better than that of other models. Soft computing tools in the form of combination of multiple nonlinear regression and M5 ’model tree were used for estimation of overtopping rate at the vertical coastal structures. For reliable and precise estimation of overtopping rate, the experimental data available in the database CLASH were used. The dimensionless overtopping rate was estimated in terms of conventional dimensionless parameters including the relative crest freeboard R_c / H_s, seabed slope tanθ, deep water wave steepness S_ (om), surf similarity ξ om (om) and local relative water depth h_t / H_s. accuracy of the new model was compared with other existing models and also evaluated with some field measurements. The results indicated that the model presented in this paper is more accurate than other existing models. the new model is better than that of other models.