Gunshot residue （GSR） constitutes a critical form of trace evidence in firearm-related forensic investigations and plays a central role in the reconstruction of shooting events. From the perspective of analytical chemistry， this review systematically summarizes recent advances in GSR detection techniques and their applications in firearm classification， aiming to provide a comprehensive reference for GSR analysis and source attribution in firearm-related cases. The characteristic components of inorganic gunshot residues （IGSR） and organic gunshot residues （OGSR）， together with their principal analytical methods， are first outlined. The advantages and limitations of conventional IGSR and OGSR detection techniques are then critically evaluated in terms of forensic applicability. Emerging approaches， including sensor-based detection systems， spatial imaging techniques， and ammunition tagging strategies， are further discussed for their potential applications in rapid screening， shooting activity reconstruction， and source attribution. Particular attention is paid to the integration of analytical data with chemometric methods， which enables the extraction of multi-dimensional compositional features and improves classification accuracy. Finally， current challenges in GSR analysis， including high-sensitivity detection， attribution of unknown samples， and cross-scenario transferability of classification models， are addressed. Future research directions emphasizing multi-technique integration， database standardization， and model robustness are proposed to support the continued advancement of GSR analysis.