The mountain permafrost distribution in the Abisko region in northern Sweden has been assessed using a combination of empirical and statistical analysis. The empirical data was obtained using the bottom temperature of snow cover (BTS) method, supported by continuous ground temperature measurements. The statistical analysis was based on 148 data points in total and used logistic regression to model the probability of permafrost occurrence. Further, Geographically Weighted Regression (GWR) was introduced as an exploratory tool for detecting non-stationarity in the relationships between permafrost and the independent variables models and showed to be a useful tool in the statistical analysis. As a result of the GWR analysis the region was divided into two subregions. The models show probabilities > 0.8 for permafrost at elevations above 1300 m a.s.l. in the western part of the region. In the eastern part, the probabilities are likely to be influenced by the potential incoming shortwave summer radiation, indicating a probability > 0.8 above 850 m a.s.l. on the north-east and east-facing slopes, above 1000 m on the west-facing slopes and above 1100 m a.s.l. on the south-facing slopes. Permafrost conditions throughout the region were found to be marginal and sensitive to current warming trends.