Abstract: With the development of electronic devices toward higher power density and miniaturization, the reliability of solder joints, which serve as critical interconnect structures, has become an increasingly important concern. This review systematically summarizes recent advances in life prediction models for solder joint reliability and compares the applicability and limitations of representative classical models, including the Coffin–Manson (C–M) model for low-cycle fatigue prediction based on plastic strain, the Engelmaier model as a modified C–M model incorporating the effect of thermal cycling frequency, and the Syed model as a cumulative damage model based on creep strain energy density. The results indicate that the Norris–Landzberg acceleration model exhibits distinct advantages in characterizing the synergistic effects of thermal stress and temperature-varying stress by simultaneously accounting for multiple parameters, including cycling frequency, temperature range, and maximum temperature. After parameter modification, this model demonstrates relatively high prediction accuracy in the storage-life assessment of electronic products, thereby providing a reference for the selection and optimization of solder joint life prediction models. On this basis, future development directions for life prediction models are further discussed. The integration of physics-informed neural networks and digital twin technologies is expected to further improve the prediction accuracy and engineering applicability of the Norris–Landzberg acceleration model under multiscale and complex operating conditions.