Cloud masks serve as a basis for estimates of cloud amount, which is an essential parameter for studying the Earth’s radiation budget. The most commonly used cloud mask is a simple thematic classification, which includes qualitative information on the presence of clouds in the satellite’s instantaneous field of view (IFOV). Cloud mask classes have to be “translated” into a quantitative measure, in order to be used for cloud amount calculations. The assignment of cloud fractions to cloud mask classes is a subjective process and increases uncertainty in cloud amount estimates. We evaluated this degree of uncertainty using the Moderate Resolution Imaging Spectroradiometer (MODIS) cloud mask product. Together with the operational MODIS cloud mask interpretation, we investigated two extreme alternatives: “rigorous” (only “confident cloudy” IFOVs were 100% cloudy) and “tolerant” (only “confident clear” IFOVs were 0% cloudy). Results showed that the range of uncertainty was 14.3% in Europe and controlled by the frequency of small convective clouds. Comparison with surface-based observations suggests that the rigorous interpretation of the cloud mask is more accurate than that used operationally for MODIS level 3 product generation. The rigorous approach resulted in the smallest bias (−0.7%), the smallest root-mean-square error (4.6%), the small standard deviation (6%), and the strongest correlation (0.935). These results suggest that for climatological applications the rigorous scenario should be considered as a more accurate “best guess” over land.