One way to demonstrate progress in a field of scientific inquiry is to show that factors believed to explain some phenomenon can also be used effectively to predict both its occurrence and its nonoccurrence. This study draws on the state strength literature to identify relevant country macrostructural factors that can contribute to different kinds and levels of intensity of conflict and country instabilities. A pattern classification algorithm-fuzzy analysis of statistical evidence (FASE)-is used to analyze the relationships between country macrostructural factors and historical instances of country instability. A split-sample validation design is used to evaluate the ability of FASE to generate competent predictions, using the standard forecasting performance metrics overall accuracy, recall, and precision. The results demonstrate the potential for FASE to accurately forecast not just the occurrence but also the level of intensity of country-specific instabilities out 5 years with about 80% overall accuracy.Since the end of the cold war, economic dislocations, civil war, famine, and ancient ethnic and religious animosities have contributed to conflict and political instability in states extending from Haiti to the vast archipelago of Indonesia. These conflicts and instabilities frequently challenge national security interests; at other times, the human rights atrocities that often accompany these dislocations offend the moral imperatives of individual states as well as the international community.Increasingly, Western powers, acting alone or in concert with international organizations, have responded to these post-cold war crises in myriad ways, including 791 AUTHOR'S NOTE: The opinions and interpretations expressed herein are my own and are not necessarily shared by the U.S. Army, the Department of Defense, or any other agency or organization of the U.S. government. For helpful comments on earlier drafts, I express my gratitude to