Low Temperature Heating (LTH) of buildings is a key feature when switching to renewable energy. Even when the capacity of LTH is high enough, LTH may adversely affect indoor thermal comfort in case buildings are not suitably insulated. This paper goes deeper into methodological issues when conducting a thermal comfort assessment. Thermal comfort is either quantified by Fanger’s Predicted Mean Vote (PMV) or ranked in building comfort classes in the adaptive model. In both cases, one of the main parameters influencing comfort is the Mean Radiant Temperature (MRT). This study addresses issues with common MRT and PMV calculations in energy simulation software. The case study is TRNSYS 17. Several MRT and PMV calculation methods are compared, showing possible draw-backs and deviations from comfort standards NEN-EN ISO 7726 and 7730. For instance, in the standard heating settings in TRNBuild only the total heating capacity is specified. The radiative part is then distributed area-weighted over opaque surfaces. A more detailed option in TRNBuild is to specify the locations of radiative gains as points. In both cases, the MRT at a comfort sphere is calculated with Gebhardt-factors instead of view-factors. The standard settings may be considered too simplified for detailed comfort studies whereas the detailed model shows deviations from comfort standards NEN-EN ISO 7726 and 7730. Therefore, two additions to these models are proposed to increase accuracy. One addition is an ordinary detailed model with radiative gains as point sources in order to retrieve all surface temperatures during a desired period of time. In the second addition walls with radiators are split-up and planes are added at the locations of radiators to generate a view-factor matrix. This can be done in TRNBuild, but also in other view-factor calculation software. From model 1 all surface temperatures are retrieved. Combined with the view-factors from model 2, the MRT can be calculated.