Nearly all societies have now committed themselves to sustainable development by integrating some form of environmental quality, social equity, and economic welfare into their day-to-day activities. As such, there remains a strong political desire for the comprehensive assessment of conditions that evaluate the current status, measure progress, and help set future development goals. Indicators have been nominated as universal tools for progressing sustainable development across scales; however, there remains no consensus regarding the best approach to their design or use. While several studies have investigated the associations between indicators of sustainable development, few have directly addressed the question of how multiple measures can be used simultaneously to assess sustainability regionally. Building upon previous studies, this paper presents a quantitative and spatial assessment of 25 multi-metric indices across 36 European nations. The goals of this research were (1) to increase understanding of indicator complexity and (2) provide an applied example of their simultaneous use for regional assessment. Global Moran's I-test and Pearson's correlation coefficient (r) analysis were used to test spatial autocorrelation and multicollinearity, respectively. From the 25 composite indices, an overall rank was also provided for each country. Lastly, Ward's cluster analysis was used to create country bundles of similarity. Our findings revealed that environmental performance index, global information networking institute coefficient, and happy planet index were numerically and spatially random. Cluster analysis revealed a four-bundle solution, while Norway, Switzerland, and Sweden ranked highest. This approach shows promise for systematically describing, visualizing, and monitoring sustainable development at the continental scale.