<p>Despite being widely adopted, horizontal-axis wind turbines face considerable challenges, especially related to the phenomenon called cascade effect. This effect is a result of the proximity between the turbine blades, causing deviations in the wind streamlines and altering the pressure distribution across the blade sections. Understanding this phenomenon is crucial to avoid overestimating the turbine’s angular velocity and to ensure accurate assessments of its efficiency. However, so far, the literature lacks reliable predictive models to address this challenge. The main contribution of this work is to develop an empirical model capable of predicting the cascade effect in horizontal-axis wind turbines with multiblades, using the Blade Element Momentum Theory (BEMT). The proposed model focuses on optimizing the necessary corrections to mitigate the cascade effect, incorporating four phenomena identified by buoyancy, solid blockage, wake blockage, and aerodynamic curvature. The equations developed in this study specifically aim to correct the angle of attack, resulting in adjusted lift and drag coefficients. This approach improves the accuracy of the aerodynamic parameters in turbines with multiple blades, considering the influence of the cascade. The validation of the proposed model was carried out by comparing it with experimental data. The experiments used straight blades with curved aerodynamic profiles, which are common in multibladed turbines. To validate the effectiveness of the developed code, data of a rotor with multiblade (<i>N</i> = 3, 6, 12, and 24) were incorporated into the BEMT model to determine power, torque, and thrust coefficients. The results demonstrated that the model is accurate to within 4.54% in correcting the cascade effect, highlighting its importance for predicting the performance of wind turbines in the global context of renewable energy production.</p>