Nickel-based polycrystalline superalloys are critical materials for hot-section components in aeroengines and gasturbines, whose high-temperature fatigue behavior directly affects the service safety and lifespan of these components. Thisarticle systematically reviews the current research status and advances in fatigue mechanical response, microstructuralevolution, damage mechanisms and failure analysis, lifetime prediction, and numerical simulation of nickel-basedpolycrystalline superalloys. Studies have shown that the macroscopic mechanical response of these alloys at hightemperatures exhibits strong path dependence, nonproportional effects, and phase-angle sensitivity, which originate from thedeep coupling between thermomechanical loading and the microstructure. At the microscale, the fatigue process involvesthe dynamic evolution of γ′/γ″ strengthening phases and competition among dislocation mechanisms, directly leading toirreversible performance degradation, such as cyclic hardening/softening. With respect to damage and failure, load phasing, by modulating the stress-temperature field, dominates the competition between intergranular and transgranular fracturemodes and may induce lifetime crossover phenomena. In terms of mechanism tracing, internal defects are the dominantfactors in crack initiation, whereas oxidation and environmental effects significantly accelerate crack propagation. Inpredictive modelling, the research paradigm is evolving from macroscopic phenomenological models to multiscale integratedmodels that incorporate physical mechanisms and data-driven intelligent approaches. Macroscopic models provide anengineering-usable framework for lifetime prediction, whereas advanced methods based on crystal plasticity theory, machinelearning, and fatigue-creep dual-parameter indicators improve the accuracy of damage evolution quantification and full-lifeprediction. Finally, a future trend toward precise lifetime prediction driven by both mechanisms and data, achieved throughthe deep integration of multiscale physical insights and artificial intelligence technologies, is proposed.