This paper explores the multifaceted complexities of belief systems across formal epistemology, artificial intelligence (AI), neuroscience, and complexity science. It emphasizes the interplay between the structural challenges of modeling beliefs, such as maintaining consistency and adapting to new information, and the inherent dynamic, hierarchical, and emergent nature of beliefs in both biological and artificial systems. The paper identifies key properties of beliefs, such as nonlinearity, self-organization, and hysteresis, and highlights the neurophysiological distinction between fast, subconscious “primal” beliefs and slower, language-mediated “conceptual” beliefs. It proposes potential pathways for developing frameworks that integrate complex-system perspectives to address the nuanced dynamics of belief systems.