Biogas, Landfill Gas, Associated Petroleum Gas, and other gases accompanying various industrial processes are potential sources of hydrogen and carbon monoxide for solid oxide fuel cells via the reforming process. As these gases contain heavy hydrocarbons, fine-tuning of steam and carbon dioxide additions and specific temperature control are necessary to avoid carbon deposition during the reforming process. Numerical simulation plays a crucial role in designing miniaturized steam reforming reactors and optimal working conditions. All simulations must account for carbon deposition. The method commonly used for thermodynamic analysis of carbon deposition includes free energy minimization or parametric equations. This paper utilizes Gaussian Process Regression (GPR) as a tool for making predictions, which reforming parameters are suitable for carrying out this process without danger of damaging catalyst due to a carbon formation. Unlike conventional methods, the GPR approach bypasses computation of equilibrium composition and therefore has the advantage of being computationally less expensive without significant loss of accuracy. This may prove to be useful, especially in large numerical models.