This study addresses the questions: In what way and to what extent does quality of life vary across the regions of the Alps and is it possible to deduce these differences from a scientific model? The study area is defined by a synthesis of the boundaries set by the Alpine Convention and the statistical units NUTS 3, and thus comprises 100 ‘Alpine regions’ in seven states. By applying many different and partly new methods of data collection, information on various topics was gathered over a two-year period. Eventually 50 complete indicator tables were compiled for all regions and the indicators grouped into twelve indicator sets: ‘Economic Power’, ‘Employment Market’, ‘Mobility’, ‘Population’, ‘Health’, ‘Education and Culture’, ‘Gender Equality’, ‘Participation’, ‘Leisure’, ‘Solar Potential’, ‘Landscape’, and ‘Biodiversity and Environmental Protection’. These indicator sets are allocated to the three dimensions ‘Economy’, ‘Socio-culture’ and ‘Environment’. From this a model emerged that incorporates the ideas of sustainability and operates with objective (comprehensible and reproducible) indicators and leaves out a concrete examination of subjective influences on quality of life. Interviews with renowned experts in the field of Alpine research served as a basis for weighting the indicators and indicator sets as well as for checking and evaluating the model. Using the basic data, a maximum of 100 points per region was awarded for each indicator, and these points were multiplied by the value derived from the weighting of the indicators by the experts. By adding the results a precise ranking could be established for every indicator set. A ranking for the three dimensions of quality of life was achieved by dividing the results of the indicator sets by the respective number of indicators used and multiplying these final results with the expert weightings of the indicator sets. The ‘Tyrol Atlas’ system offers a valuable help for visualizing the results, which are not only presented as textual analyses, but also with the help of tables, graphics and especially maps. The distribution patterns of the results for the individual indicators, indicator sets, and dimensions allow conclusions on the different dimensions of quality of life. Regional patterns may even point to ‘overall winners’ or ‘losers’. The study did not, however, set out to come up with an overall ranking ‘Quality of Life within the Alpine Space’, and it does not seem feasible at present either. To this end, further intensive efforts in the field of sustainability research will be needed in future. Ultimately the following short rule applies: No quality of life without sustainability, no research on quality of life without integrative geography.