The control problem in wave energy continues to remain an open question. This is mainly attributed to the difficulties associated with developing effective, yet economically viable, wave energy-harnessing control strategies, such as resource irregularity, the multidisciplinary nature of the system, and dynamic model uncertainties and ambiguities. Herein, a maximum energy-capturing approach for heaving wave energy converters (WECs) using an estimator-based finite control set model predictive control (FCS-MPC) is proposed. The proposed control strategy utilizes an elaborate nonlinear wave-to-wire model of a heaving WEC. The FCS-MPC is formulated such that a control command trajectory is not required; instead, it searches for the optimum control law—in the form of switching functions—that maximizes the WEC converted electrical energy while imposing soft constraints on the states of the power take-off (PTO) mechanism. Current transducers are deployed to measure the PTO three-phase currents and both mechanical and electrical variables required by the FCS-MPC strategy are estimated using an electrical-based extended Kalman filter (E-EKF). Simulations were performed to assess the effectiveness of the proposed control strategy. Results presented herein clearly show that the proposed referenceless FCS-MPC managed to produce 10%–23% more energy compared with benchmark resistive loading-based techniques with both fixed and variable wave frequency capabilities while utilizing 18%–45% less PTO resources.