Abstract: Heavy metal ions pose significant threats to human health due to their persistence, bioaccumulation, and toxicity, creating an urgent need for rapid, sensitive, and reliable analytical methods. Surface-enhanced Raman spectroscopy (SERS) has emerged as a powerful technique for detecting heavy metal ions, offering ultrahigh sensitivity, molecular fingerprinting capabilities, and rapid, non-destructive analysis. In recent years, substantial advances in SERS-based sensing have led to the development of multiple detection strategies based on distinct mechanisms. This review systematically summarizes research progress in the SERS detection of heavy metal ions over the past decade. Three representative strategies-signal intensity transduction, chemical bonding, and thin-layer solid-state transformation-are discussed regarding their sensing mechanisms, SERS substrate design, and representative applications. Their respective advantages and limitations are compared in terms of analytical performance, including sensitivity, selectivity, and linear detection range. Additionally, recent advances in chemometric and AI-assisted SERS spectral analysis are reviewed, with particular emphasis on heavy metal ion identification, quantitative analysis, and the interpretation of complex spectral data. Finally, key challenges related to sensing mechanisms, complex matrix analysis, standardization, and the deep integration of AI with SERS are discussed, and future research directions are highlighted. By providing a comprehensive overview of both sensing strategies and spectral data analysis, this review aims to offer theoretical guidance and new perspectives for developing high-performance SERS platforms for heavy metal ion detection and their practical applications.