Objective This study aimed to analyze the differences between the distribution of Traditional Chinese Medicine (TCM) syndrome elements and salivary microbiota between the individuals with pulmonary nodules and those without. Additionally, it seeked to explore the potential correlation between the distribution of Traditional Chinese Medicine (TCM) syndrome elements and salivary microbiota in patients with pulmonary nodules. Methods We retrospectively recruited 173 patients with pulmonary nodules (PN) and 40 healthy controls (HC). The four diagnostic information was collected from all participants, and syndrome differentiation method was used to analyze the distribution of Traditional Chinese Medicine (TCM) syndrome elements in both groups. Saliva samples were obtained from the subjects for 16S rRNA high-throughput sequencing to obtain differential microbiota and to explore the correlation between Traditional Chinese Medicine (TCM) syndrome elements and salivary microbiota in the evolution of the pulmonary nodule disease. Results The study found that in the PN group, the primary Traditional Chinese Medicine (TCM) syndrome elements related to disease location were the lung and liver, and the primary Traditional Chinese Medicine (TCM) syndrome elements related to disease nature were yin deficiency and phlegm. In the HC group, the primary Traditional Chinese Medicine (TCM) syndrome elements related to disease location were the lung and spleen, and the primary Traditional Chinese Medicine (TCM) syndrome elements related to disease nature were dampness and qi deficiency. There were differences between the two groups in the distribution of Traditional Chinese Medicine (TCM) syndrome elements related to disease location (lung, liver, kidney, exterior, heart) and disease nature (yin deficiency, phlegm, qi stagnation, qi deficiency, dampness, blood deficiency, heat, blood stasis) (P<0.05). The species abundance of the salivary microbiota was higher in the PN group than that in the HC group (P<0.05), and there were significant differences in community composition between the two groups (P<0.05). Correlation analysis using multiple methods, including Mantel test network heatmap analysis and Spearman correlation analysis and so on, showed that in the PN group, Prevotella and Porphyromonas were positively correlated with disease location in the lung, and Porphyromonas and Granulicatella were positively correlated with disease nature in yin deficiency (P<0.05). Conclusion The study concludes that there are notable differences in the distribution of Traditional Chinese Medicine (TCM) syndrome elements and the species abundance and composition of salivary microbiota between patients with pulmonary nodules and healthy individuals. The distinct external syndrome manifestations in patients with pulmonary nodules, compared to healthy individuals, may be a cascade event triggered by changes in the salivary microbiota. The dual correlation of Porphyromonas with both disease location and nature suggests that changes in its abundance may serve as an objective indicator for the improvement of symptoms in patients with yin deficiency-type pulmonary nodules.