Minocycline (Mino) is an antibiotic with neuroprotective, anti-inflammatory, and antioxidant properties. This study investigated the protective effects of Mino against hydrogen peroxide (H2O2)-induced oxidative damage in dermal fibroblast cells and analyzed these effects using Raman spectroscopy, principal component analysis (PCA), and machine learning (ML). L929 fibroblast cells were evaluated using MTT and scratch wound-healing assays. The production of reactive oxygen species (ROS) and the process of apoptosis were evaluated through the use of 2',7'-dichlorofluorescein diacetate (DCFH-DA) and Annexin V labelling, respectively. The mRNA expression levels of Nrf2, Hmox1, Nqo1, and Col1a were analyzed through quantitative real-time polymerase chain reaction (qRT-PCR). Raman spectroscopy detected molecular alterations, while PCA and ML classified spectral variations. Mino reduced H2O2-induced cellular toxicity, ROS levels, and apoptosis while enhancing fibroblast migration. It significantly upregulated Nrf2 and Hmox1 mRNA under oxidative stress and increased Col1a expression when applied alone. Raman spectroscopy revealed biochemical changes in lipids, proteins, and nucleic acids. PCA distinguished treatment groups, showing Mino-treated cells closely resembled controls. The SVM attained 90.10 % classification accuracy, underscoring the efficacy of Raman-based computational analysis. The findings collectively highlight the potential of Raman spectroscopy, PCA, and ML as a sensitive, label-free approach for monitoring molecular changes, thereby supporting the therapeutic potential of Mino in oxidative stress-related therapies.