Abstract: In this work, two new entropic regularization technique are introduced. They represent a generalization of the standard MaxEnt regularization method, and allow for a greater flexibibility for introducing any prior information about the expected structure of the true physical model, or its derivatives, into the inverse procedure. The first technique is based on the minimization of the entropy of the vector of the first-defferences of the unknown parameters. Adopting the standard terminology, it is called the minimum first-order entropy method (MinEnt-1). To illustrate the essential feature of the method, the MinEnt-1 is applied to reconstruction of the two-dimensional geoeletric conductivity distributions from magnetotelluric data. The second technique is based on the maximization of the netropy of the vector of second-differences of the unknown parameters, and is denoted as MaxEnt-2 method. The MaxEnt-2 method is applied to the retrieval of vertical profiles of temperature in the atmosphere from remote sensing data.