The sun is a plenty and popular source of renewable energy. To transform solar energy into electricity it is necessary to use photovoltaic (PV) panels which in turn have flow efficiency and therefore do not provide maximum power. Maximum power depends on temperature and solar radiation. Changes in these  environmental factors require an algorithm to find the Maximum Power Point (MPP) where maximum power can be extracted. The algorithm is called the Maximum Power Point Tracking (MPPT). Through MatLab=Simulink the MPPT algorithm based on the Kalman Filter was implemented. The MPPT algorithm is essential for the maximum use of solar energy and therefore plays an important role for the feasibility and competitiveness of PVs in renewable energy. This article proposes a MPPT based on the kalman filter that has the advantage of efficiently estimating variables based on measurements with statistical noise, in this case measurements of solar irradiation and temperature. The results show efficiency because the relative errors are less than 1.13% compared to results obtained from simulink.