Maximum power point tracking plays an important role for Photovoltaic (PV) energy pumping systems because it optimizes the power output from a Photovoltaic system for a given set of conditions. This thesis presents model predictive controller (MPC) of maximum power point tracking (MPPT) for a standalone solar water pumping system. Model predictive control (MPC) is advanced control that predicting the future behavior of the desired control variables. This work focused on designing of MPC controller method to get maximum amount of power for Addis Alem kebele appropriate power for the required amount of demand to pump water from the ground to 394 residential house hold needs. In this work scaling and sizing the whole components of the standalone solar water pumping system, such as, PV panel, boost converter and inverter is applied to generate a 2.927 kW power by using a boost converter as a supporter for MPPT algorithm by adjusting the duty cycle of the boost converter to maximize the output to the inverter which is feeding an alternative 2.63 kW current load would achieved. After sized and designed the proposed system components, each System elements are individually modeled in MATLAB/SIMULINK and then connected to evaluate performance under different environmental conditions. First, each technique is compared with the direct connection matched system. The results show that the direct connection PV system response oscillates far from the tracking point and the MPC controller method dynamics responses will be around the MPP under different level of temperature and irradiation. The output response of MPC controller for PV system will evaluate be through simulation studies.