Abstract: As a core transcription factor governing cellular stress responses, Nrf2 plays an indispensable role in redox regulation and the maintenance of cellular homeostasis, thereby representing a critical therapeutic target for numerous diseases. Natural products constitute a rich reservoir of Nrf2 modulators; however, efficiently identifying bioactive compounds with genuine Nrf2-targeting activity remains challenging, owing to the diversity of screening approaches and the absence of standardized evaluation criteria. This review systematically categorizes both conventional and modern intelligent screening strategies and provides a critical comparison of their respective advantages and limitations. Source-oriented discovery, when implemented as a pre-screening step, can effectively narrow the candidate scope and improve screening efficiency. Furthermore, we analyze the current bottlenecks in natural product discovery from three perspectives, including technical constraints, insufficient mechanistic elucidation, and poor translational outcomes, and propose viable directions for future development. Collectively, the hierarchical integration of AI-driven virtual screening, biosensor-based binding assays and multi-omics mechanistic profiling, along with functional validation at both cellular and animal levels, offers a feasible technological route toward the efficient discovery of Nrf2-targeting natural products.