This paper deals with the problem of the optimization of the power, delivered by the photovoltaic panel (PVP). To achieve this aim, a neural network estimator (NNE), followed by a conversion coefficient and a calculation stage of the optimal duty cycle, has been developed. The NNE is used to calculate the open circuit voltage corresponding to each solar radiation and to various value of temperature, based only on the standard open circuit voltage. A coefficient, determining for each solar radiation the voltage of the maximum power directly from the open circuit voltage, is estimated by a practical test. Finally, the optimal duty cycle is, next, determined by the input/output equation of boost converter. The system performance, under different scenarios, has been checked carrying out Matlab/Simulink simulations, using an existing photovoltaic model and real weather data, and comparing the simulation results with the real one. The results demonstrate the effectiveness of the present approach. The efficiency of the proposal maximum power point tracking (MPPT) is proved and it showed that this controller can generate almost 99% of the real PVP maximum power.