[en] The new unfolding method based on Shanon's information theory is obtained and appropriate numerical code which can be preeminently applied in fast neuron spectrometry based on proton recoil is realised. Principle of maximum entropy and maximum likelihood are used together. Unknown group density distribution functions, which are considered using only constraint of knowing mean value. obtained distributions are consistent to available information (counts in MCA), while being maximally noncommittal with respect to all other unknown circumstances. For maximum likelihood principle, distribution functions around mean value of counts in the channels of MCA are taken to be Gauss function shaped. Optimum non-negative solution is searched by means of Lagrange parameter method. Nonlinear system of equations is solved using gradient and Newton iterative algorithm. Error covariance matrix is obtained too. (author)