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Explore the challenges of rational inference in complex sciences through this thought-provoking 47-minute lecture by Amos Golan, an External Professor at the Santa Fe Institute and faculty at American University. Delve into the complexities of reasoning, modeling, and inference in the face of imperfect, limited, or incomplete information. Examine the need for a coherent, decision-theoretic framework for rational inference in both theoretical and empirical contexts. Consider key questions such as defining and implementing rational approaches to inference, handling model misspecifications, and addressing issues of uncertainty, robustness, and sensitivity analysis. Gain insights into the universal problem of insufficient information across disciplines and explore potential solutions through rational inference methods. Trace the historical roots of this dialogue from the work of Neyman, Pearson, and Fisher to contemporary advancements in the field.