Underwater Optical Wireless Communication (UWOC) becomes an emerging underwater communication technology, with high-data rates over relatively medium transmission ranges. When optical wireless signal transmitted in ocean water channel, it will suffer from drastic scattering and absorption due to water molecules, dissolved particles, air bubbles, and turbulence. Absorption and scattering of the transmitted wireless optical signal in underwater channel led to attenuation in optical signal power. Optical signal attenuation over underwater channel is an aggregate of` different parameters effects that changed frequently, then practical measuring of this attenuation is complicated, difficult, expensive, and time-consuming process. In this work, improved neural network optimized with future search algorithm (FANN) was proposed, as an efficacious solution to obtain an accurate, relabel values of attenuation coefficient in different water types and conditions. The proposed FANN model provides a good much results to the practical measured values. The performance of the proposed FANN model was evaluated using mean square error (MSE), root mean square error (RMSE) and mean absolute error (MAE) error indices. The errors in attenuation coefficient values obtained by the proposed FANN model had been calculated and its values are very acceptable which are lie lower than 10-4. The performance of the proposed FANN model shows excellent results which indicate the superior performance of the proposed FANN model.