Abstract: A technique for the estimation of the phase function in natural waters, based on the least square estimator, which is associated to a regularization function (maximum entropy principle), is presented. In the analyses, noise corrupted synthetic data (radiances and irradiances) were used. These data were generated by the same analytical forward model employed in the inversion and implemented by PEESNC code. The inverse problem is iteratively solved by the quasi-Newtonian optimization algorithm. The recovery of the phase function is successfully performed for the selected sample problem.