Nuclear waste repositories are being considered by many countries to be the best solution to deal with the increasing amount of High-Level Waste (HLW) from nuclear power plant operation and decommissioning. The Swiss repository concept has been assessed since the '90s in Mont Terri Underground Rock Laboratory (URL) via numerous in-situ experiments. Among the different experimentations taking place in the URL, the Full-scale Emplacement (FE) is an in-situ experiment that mimics the construction, backfilling, and early-stage evolution of the repository tunnel. Close and far fields have been extensively instrumented to identify the main repository-induced effects (RIE) associated with the excavation and waste decaying. In this framework, modeling the FE experiment is extremely valuable to scope the main parameters acting on the RIE in a relatively small timeframe. In the present research, we use the FE experiment database to validate a coupled Thermo-HydroMechanical (THM) finite element model of the problem and quantify the inherent uncertainties. To do so, we first performed a sensitivity analysis on the parameter domain to identify the parameters prone to be optimized using a variance-based strategy. Once the main parameters influencing the THM behavior were identified, a Bayesian inference approach was adopted to estimate the modeling uncertainty by comparing the numerical results to the experimental monitoring data. Results showed good agreement with the experimental data for temperature and pore-pressure close field sensors with relatively small model variance and showed the applicability of such a modeling approach for RIE assessment.