This paper proposes a cost-effective maximum power point tracking (MPPT) technique for photovoltaic (PV) systems that minimizes hardware requirements by using fewer sensors. The method employs a modified SEPIC converter together with a Model Predictive Control (MPC)–based MPPT algorithm to achieve efficient power extraction under varying environmental conditions. The proposed approach requires only a single voltage sensor and a single current sensor—significantly reducing hardware complexity compared to conventional MPPT techniques. The modified SEPIC converter is used to regulate the PV system’s voltage and current, while the MPC-based MPPT algorithm dynamically adjusts the converter operation to continuously track the maximum power point (MPP). By utilizing a predictive model of the PV system, the algorithm anticipates system behavior based on real-time sensor data, enabling precise and rapid MPPT action. Real-time operation allows for instantaneous control updates, ensuring optimal power extraction at all times. Simulation and hardware results confirm that the proposed technique effectively identifies and tracks the MPP using only two sensors, thus reducing system cost while maintaining high performance. The integration of the MPC-based MPPT algorithm with the modified SEPIC converter demonstrates superior efficiency and improved power extraction compared to traditional MPPT methods.