This thesis identifies a discrepancy in the understanding of peace as a need for further efforts to be made in both the conceptualization and operationalization of what peace is. Working from the pluralistic multidimensional view of what peace could be defined as, dictated by the works of Dietrich (2014), Kovacs-Söderberg and Höglund (2010) and Davenport et al. (2018), this thesis set out to explore structures present in the descriptive variables of peacefulness found in the Global Peace Index data set. Through a multivariate cluster analysis, six clusters emerged. These inhibited differing magnitudes of the set of variables, that served as the basis for profiling and labelling of the clusters. Five of the clusters were defined as varying levels of internal and external qualities, behaviors and attitudes. The sixth cluster served as a more peaceful category, containing most countries traditionally understood as peaceful. The thesis concluded in a result that encourages the use of the clustering as a tool for peace categorization but lacked in the power of explaining variations of the most peaceful category. Concluding that the included variables proved to be inadequate when attempting to uncover variations of observations that are considered more peaceful, suggesting that additional variables are needed to capture the variety between these observations.