ABSTRACTObjective: Performance analysis is vital in the health sector owing to health expenditures, increased quality demands, and competition. In thisstudy, we aimed to evaluate the relative efficiencies of different countries that use similar health status indicators.Material and Methods: A K-means clustering algorithm with five different variables was used to ensure homogeneity among the countries selected for comparison. The resulting clusters were analyzed using an input-oriented data envelopment analysis with four inputs and three outputvariables for evaluating the relative efficiencies of countries within each cluster. Accordingly, input variables, such as current health expenditureper capita (current US$), hospital beds (per 1000 people), physicians (per 1,000 individuals), and nurses and midwives (per 1,000 people); andoutput variables, such as life expectancy at birth, maternal survival rate (per 100,000 live births), and infant survival rate (per 1,000 live births)were determined, and efficiency analysis was performed.Results: The countries were first clustered into three homogenous groups using a k-means clustering algorithm. For 177 countries whose datawere accessible (out of 189 countries), the first, second, and third clusters comprised of 74, 55, and 48 countries, respectively. Then, scale efficiency,pure technical efficiency, and technical efficiency scores were obtained by data envelopment analysis. In the first cluster, 31 countries (41.89%)were categorized as pure technical efficient, whereas in the second and third clusters, 20 (37.03%) and 23 (47.92%) countries were categorized aspure technical efficient, respectively.Conclusion: Cross-country studies are crucial for countries for the assessment of comparative positions and for improvement of their healthstatus accordingly. Policymakers can compare the relative efficiency of their countries with other countries that possess similar health resources.Accordingly, they can set achievable targets by referring data of efficient countries