Objective: Periodontitis is known to be associated with preterm birth. Gastroesophageal reflux disease is common in pregnancy and related to periodontitis. Little study is done the relationship between gastroesophageal reflux disease, periodontitis, and preterm birth. This study uses popular machine learning methods for analyzing preterm birth, gastroesophageal reflux disease, and periodontitis. Methods: Data came from Anam Hospital in Seoul, Korea, with 731 obstetric patients during January 5, 1995-August 28, 2018. Six machine learning methods were applied and compared for the prediction of preterm birth. Variable importance, the effect of a variable on model performance, was used for identifying major determinants of preterm birth. Analysis was done on June, 2019. Results: In terms of accuracy, the random forest (0.8681) was similar with logistic regression (0.8736). Based on variable importance from the random forest, major determinants of preterm birth are delivery and pregestational Body Mass Index (BMI) (0.1426 and 0.1215), age (0.1211), parity (0.0868), predelivery systolic and diastolic blood pressure (0.0809 and 0.0763), twin (0.0476), education (0.0332) as well as infant sex (0.0331), prior preterm birth (0.0290), progesterone medication history (0.0279), endoscopic symptom (0.0274), gastroesophageal reflux disease (GERD) (0.0242), Helicobacter pylori (0.0151), region (0.0139), calcium-channel-blocker medication history (0.0135) and gestational diabetes mellitus (0.0130). Periodontitis was reported as 22th ranked (0.0084). Conclusion: With preterm birth, GERD and periodontitis would be associated with BMI, hypertension and diabetes. Interestingly, periodontitis was not as affective as GERD for preterm birth. Our data suggest that the presence of GERD would handle the role of periodontitis, known risk factor in preterm birth.