In the Bayesian approach to solving inverse problems to parameter estimation, the quantities we seek to retrieve are considered as random variables. The randomness includes the uncertainty regarding their true values. We intend to use this approach to perform inversion of coupled radiative and heat transfer models for asteroid regoliths and lakes. The Bayesian inversion of this kind of models allows estimating optical and thermodynamic properties of the systems considered, and also allows finding any correlation among these properties; that would be quite difficult to find with the classical approaches.