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Based on the example of the evaluation of service organization models, this article shows how a configurational approach overcomes the limits of traditional methods which for the most part have studied the individual components of various models considered independently of one another. These traditional methods have led to results (observed effects) that are difficult to interpret. The configurational approach, in contrast, is based on the hypothesis that effects are associated with a set of internally coherent model features that form various configurations. These configurations, like their effects, are context-dependent. We explore the theoretical basis of the configuration approach in order to emphasize its relevance, and discuss the methodological challenges inherent in the application of this approach through an in-depth analysis of the scientific literature. We also propose methodological solutions to these challenges. We illustrate from an example how a configurational approach has been used to evaluate primary care models. Finally, we begin a discussion on the implications of this new evaluation approach for the scientific and decision-making communities.