A variety of numerical, analytical and statistical models have been developed for estimating the mean annual permafrost table temperature (MAPT) and active-layer thickness (ALT). These tools typically require at least a few ground physical properties, such as thermal conductivity, heat capacity, water content or bulk density, as input parameters in addition to temperature variables, which are, however, unavailable or unrepresentative at most sites. Ground physical properties are therefore commonly estimated, which may yield model outputs of unknown validity. Hence, we devised two simple analytical–statistical models (ASMs) for estimating MAPT and ALT, which are driven solely by pairwise combinations of thawing and freezing indices in the active layer; no ground physical properties are required. ASMs reproduced MAPT and ALT well in most numerical validations, which corroborated their theoretical assumptions under idealized scenarios. Under field conditions of Antarctica and Alaska, the mean ASMs deviations in MAPT and ALT were less than 0.03 °C and 5 %, respectively, which is similar or better than other analytical or statistical models. This suggests that ASMs can be useful tools for estimating MAPT and ALT under a wide range of climates and ground physical conditions.