Introduction: Cesarean section is one of the most common obstetrical interventions that has been performed at an increasing rate globally, due to both medical and non-medical reasons. This study aims to develop a prediction tool for pregnant women potentially needing c-section, such that necessary preparations from the mothers, families, and health providers can be made. Methods: A total of 603 pregnant women were recruited in the first phase of c-section prediction tool development. The association between the maternal and fetal factors on the risk of c-section were analyzed, followed by a stepwise multivariate regression analysis. In the next phase, 61 pregnant women were enrolled for external validation. Discrimination was assessed using area under the curve. The calibration plot was then made and assessed using the Hosmer–Lemeshow test. Results: There were 251 (41.6%) cases of vaginal delivery and 352 (58.4%) of c-section assessed. Multivariate analysis showed that gestational age < 37 wg (OR: 1.66, 95% CI: 1.10–2.51), pre-pregnancy body mass index (underweight) (OR: 0.40, 95% CI: 0.22–0.76), no history of vaginal delivery (OR: 2.66, 95% CI: 1.76–4.02), history of uterine surgery (OR: 8.34, 95% CI: 4.54–15.30), obstetrical complications (OR: 5.61, 95% CI: 3.53–8.90), birthweight ⩾ 3500 g (OR: 4.28, 95% CI: 2.16–8.47), and non-cephalic presentation (OR: 2.74, 95% CI: 1.53–4.89) were independently associated with c-section delivery. Those parameters were included in a 7-item scoring tool, with consecutive predictive scores of 1,–1,2,3,3,2,2,1. The area under the curve result was 0.813 (95% CI: 0.779–0.847), indicating a good predictive ability. The external validation showed AUC: 0.806, 95% CI: 0.694–0.917, Hosmer–Lemeshow test p = 0.666 and calibration plot coefficient of r = 0.939. Conclusion: A total of 7 maternal-fetal factors were found to be strongly associated with c-section delivery, including gestational age < 37, maternal underweight body mass index, previous uterine surgery, obstetrical complications, birthweight ⩾ 3500, history of vaginal delivery, and non-cephalic presentation. Using these factors, a prediction tool was developed and validated with good quality. © The Author(s) 2021.