In this study, we sought to find novel bacterial and metabolic hallmarks for bacterial vaginosis (BV). We studied the vaginal microbiome and metabolome of vaginal fluids from BV-affected patients (n = 43) and healthy controls (n = 37) by means of an integrated approach based on quantitative polymerase chain reaction (qPCR) and proton nuclear magnetic resonance ((1)H-NMR). The correlations between the clinical condition and vaginal bacterial communities were investigated by principal component analysis (PCA). To define the metabolomics signatures of BV, 100 discriminant analysis by projection on latent structure (PLS-DA) models were calculated. Bacterial signatures distinguishing the health condition and BV were identified by qPCR. Lactobacillus crispatus strongly featured the healthy vagina, while increased concentrations of Prevotella, Atopobium and Mycoplasma hominis specifically marked the infection. (1)H-NMR analysis has led to the identification and quantification of 17 previously unreported molecules. BV was associated with changes in the concentration of metabolites belonging to the families of amines, organic acids, short chain fatty acids, amino acids, nitrogenous bases and monosaccharides. In particular, maltose, kynurenine and NAD(+) primarily characterised the healthy status, while nicotinate, malonate and acetate were the best metabolic hallmarks of BV. This study helps to better understand the role of the vaginal microbiota and metabolome in the development of BV infection. We propose a molecular approach for the diagnosis of BV based on quantitative detection in the vaginal fluids of Atopobium, Prevotella and M. hominis, and nicotinate, malonate and acetate by combining qPCR and (1)H-NMR.