Permafrost in the northern high latitudes is experiencing accelerated warming, casting important implications for carbon–climate feedback and ecosystem stability. Integrating three open-access permafrost products, this study generates an ensemble permafrost dataset of permafrost percent (PP) and mean annual ground temperature (MAGT), and proposes a Permafrost Thaw Index (PTI) to measure thaw vulnerability in a two-tier ranking system. Sixteen open-access datasets derived primarily from satellite observations are ensembled to represent environmental conditions, including land surface temperature (LST), vegetation dynamics, snow cover, freeze–thaw state, soil properties, and topography. An ensemble machine learning approach, XGBoost, is employed to predict PTI from these datasets with an overall accuracy of 91.8%. Thermal variables, particularly LST, LST trends, and frozen days, contribute most strongly to PTI prediction. The PTI map reveals clear latitudinal gradients and regional variations in alignment with eco-climatic transitions. The total permafrost coverage in the northern high latitudes (> 45°N) is approximately 18.7 million km<sup>2</sup>. About 41.4% remains highly stable, while nearly half is subject to high thaw pressure. The most stable conditions persist in the High Arctic tundra of North America, the Arctic East Siberia, and the high-elevation alpine tundra of North Asia. The highest vulnerability occurs along the southern margins dominated by boreal and montane forests. A comparison of the predicted PTI with borehole records from 26 established stations reveals strong agreement (Spearman's r = 0.69). This study demonstrates the value of multi-source open satellite data in permafrost research. The proposed PTI framework provides a scalable approach for monitoring permafrost dynamics and supporting climate impact assessments over the northern high latitudes. The ensemble products of this study, including the PTI map and the ensemble land cover and permafrost distributions (PP and MAGT), can be freely downloaded at <a href="https://doi.org/10.5281/zenodo.19148960" target="_blank" rel="noopener">https://doi.org/10.5281/zenodo.19148960</a>.