This paper presents a predictive braking control algorithm for electric vehicles with redundant braking actuators, composed of friction brake actuator(s) and electric motor(s). The proposed algorithm is based on a model predictive control framework and is able to optimally tackle several control goals, such as maximization of energy recuperation and wheel slip regulation, while taking into account actuation dynamics and constraints. The braking control algorithm was simulated and experimentally validated on the ROMO research vehicle. The obtained results demonstrate that in comparison with state-of-the-art control techniques, the proposed model predictive control approach is able to reduce the torque tracking error up to 60%, and improve the deceleration during emergency braking up to 10%.