This work aims to present a model-free predictive control (MF–PC) technique that is robust to parameter and model changes to control a boost converter. The MF–PC proposed is based on calculating and updating the value of the current slope in the inductor at each sampling instant and using it to predict the future value of the current to define the optimal state to apply in the next step. To evaluate the performance of this proposal, a fair comparison is made between MF–PC and classical finite control set model predictive control (FCS–MPC) under reference changes and physical converter parameter variations in a boost converter. The experimental results show that the proposed method is robust against parameters and model changes compared to FCS–MPC. Additionally, the proposed controller reduces the number of sensed variables compared to the conventional FCS–MPC and has the simplicity required for converters operating at high frequencies.