The severe COVID‐19 pandemic requires the development of novel, rapid, accurate, and label‐free techniques that facilitate the detection and discrimination of SARS‐CoV‐2 infected subjects. Raman spectroscopy has been used to diagnose COVID‐19 in serum samples of suspected patients without clinical symptoms of COVID‐19 but presented positive immunoglobulins M and G (IgM and IgG) assays versus Control (negative IgM and IgG). A dispersive Raman spectrometer (830 nm, 350 mW) was employed, and triplicate spectra were obtained. A total of 278 spectra were used from 94 serum samples (54 Control and 40 COVID‐19). The main spectral differences between the positive IgM and IgG versus Control, evaluated by principal component analysis (PCA), were features assigned to proteins including albumin (lower in the group COVID‐19 and in the group IgM/IgG and IgG positive) and features assigned to lipids, phospholipids, and carotenoids (higher the group COVID‐19 and in the group IgM/IgG positive). Features referred to nucleic acids, tryptophan, and immunoglobulins were also seen (higher the group COVID‐19). A discriminant model based on partial least squares regression (PLS‐DA) found sensitivity of 84.0%, specificity of 95.0%, and accuracy of 90.3% for discriminating positive Ig groups versus Control. When considering individual Ig group versus Control, it was found sensitivity of 77.3%, specificity of 97.5%, and accuracy of 88.8%. The higher classification error was found for the IgM group (no success classification). Raman spectroscopy may become a technique of choice for rapid serological evaluation aiming COVID‐19 diagnosis, mainly detecting the presence of IgM/IgG and IgG after COVID‐19 infection.