Volume 25 discusses strategies to avoid the conventional, and still dominant logic of using symmetric thinking and multiple regression analysis and to make use of asymmetric thinking, complexity theory tenets, and qualitative comparative analysis (QCA) to achieve more useful forecasts of what is possible and likely to happen. Asymmetric modelling formally recognizes that the configurations of causes of undesirable outcomes are not the mirror opposites of the configurations of causes of desirable outcomes. QCA tools enable researchers and decision-makers to move away from thinking of relative sizes of influences of independent variables to ask the better question: what conditions come together that cause great outcomes to occur? The authors also describe how to build models that consistently produce undesirable/bad outcomes. This book describes tools that are useful for decision-makers to improve their understanding of what is likely to happen in different configurations of contexts and decisions and to improve their forecasting abilities substantially.