The work performed in this thesis allows the assessment of PICA thermal conductivity ratio and cold wall stagnation point heat flux by harnessing the powerful tool of Bayesian Inference. As part of the inference framework, that has been implemented on MATLAB using UQLab, the McDougall thermal model has been used. Before implementing it in the framework, a study about the model precision (for the calculation of temperature histories at specific thermocouple locations) when varying mesh size and timestep has been performed. By exploring the uncertain nature of these parameters, the inference framework allowed the definition of the posterior distributions of α and q0, using available experimental results from (1).