Reservoir permeability serves as a critical parameter for unconventional reservoir characterization and hydrocarbon recovery optimization. However, complex petrophysical mechanisms and multifactorial coupling make its seismic prediction face significant challenges. This review comprehensively synthesized advances and limitations across three dominant methodologies: (i) dispersion/attenuation-based methods, limited by petrophysical assumptions, scaling issues, and non-uniqueness; (ii) pore structure-constrained methods, enhancing prediction accuracy but hindered by oversimplification and high-dimensional inversion instability; and (iii) artificial intelligence frameworks, offering data efficiency yet challenged by error propagation, overfitting vulnerability, and geologically implausible extrapolation. Comparative analysis revealed core bottlenecks in inadequate multiscale coupling between petrophysical mechanisms and data-driven approaches. These challenges are compounded by the absence of cross-disciplinary validation frameworks. To address these challenges, this review integrated interdisciplinary perspectives from seismic exploration, petrophysics, and machine learning. It proposed a tripartite permeability prediction paradigm unifying physical mechanisms, data-driven techniques, and engineering validation. This framework encompasses: first, advancing multi-porosity fluid-solid coupling theory and pore structure-constrained rock physics models; second, constructing physics-guided multimodal learning architectures that deeply embed differentiable physical laws (e.g., Darcy-Biot theory) within cross-scale physics-informed neural networks, coupling microscopic pore network simulations with macroscopic seismic responses; third, establishing a closed-loop workflow covering digital rock core simulations, blind well testing validation, production history matching, and dynamic data-driven evolution, thereby forming a quantifiable and iteratively upgradable technological system. This paradigm provides a multiscale approach for accurately characterizing permeability in unconventional reservoirs, and it establishes foundational theoretical principles and delineates practical implementation pathways for economically viable unconventional resource development.