Thermal conductivity data used in basin-scale modeling have relatively large uncertainties, even if based on good-quality laboratory data. Consequently, these uncertainties in thermal conductivity may lead to similar magnitude relative uncertainties in any thermal history reconstruction. The potential scale of these uncertainties is considered, and an inverse thermal history modeling approach is combined with Monte Carlo sampling to assess the thermal history uncertainties in a real-data situation, using vitrinite reflectance data to constrain the thermal history model. The results show that the uncertainties are considerably less than what might be expected from a linear error analysis on the thermal conductivities. This reassuring inference arises as a consequence of the feedback between thermal conductivity and heat flow, which vary sympathetically to maintain an overall similar thermal history.