This study aimed to find a potential biomarker that can be used to diagnose prediabetic condition by comparing the salivary bacterial microbiomes between Thai dental patients with normoglycemia (NG) and those with potential prediabetes (PPG) conditions. Thirty-three subjects were randomly recruited. Demographic data were collected along with oral examination and unstimulated salivary collections. The salivary bacterial microbiomes were identified by high-throughput sequencing on the V3–V4 region of the bacterial 16S rRNA gene. Microbiomes in this study were composed of 12 phyla, 19 classes, 29 orders, 56 families, 81 genera, and 184 species. To check the validity of the selection criterion for prediabetes, we adopted two separate criteria to divide samples into PPG and NG groups using glycated hemoglobin A1c (HbA1c) or fasting plasma glucose (FPG) levels. Using the HbA1c level resulted in the significant reduction of Alloprevotella, Neisseria, Rothia, and Streptococcus abundances in PPG compared with those in NG (p-value < 0.05). On the other hand, the abundance of Absconditabacteriales was significantly reduced whereas Leptotrichia, Stomatobaculum, and Ruminococcaceae increased in the PPG group when the samples were classified by the FPG level (p-value < 0.05). It is implied that the group classifying criterion should be carefully concerned when investigating relative abundances between groups. However, regardless of the criteria, Rothia is significantly dominant in the NG groups, suggesting that Rothia might be a potential prediabetic biomarker. Due to the small sample size of this study, further investigation with a larger sample size is necessary to ensure that Rothia can be a potential biomarker for prediabetes in Thai people.