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Predictive modeling of neuroimaging data (predictive neuroimaging) for evaluating individual differences in various behavioral phenotypes and clinical outcomes is of growing interest. However, the field is experiencing challenges regarding the interpretability of results. Approaches to defining the specific contribution of functional connections, regions, and networks in prediction models are urgently needed, potentially helping to explore underlying mechanisms. In this article, we systematically review methods and applications for interpreting brain signatures derived from predictive neuroimaging, based on a survey of 326 research articles. Strengths, limitations, and suitable conditions for major interpretation strategies are also deliberated. An in-depth discussion of common issues in the existing literature and corresponding recommendations to address these pitfalls are provided. We highly recommend exhaustive …