How this instrument works
This calculator implements the Grobman et al. logistic regression model, published in Obstetrics & Gynecology in 2007 and developed by the Maternal-Fetal Medicine Units (MFMU) Network from roughly 7,660 women attempting a trial of labor after one prior cesarean. Seven inputs — maternal age, pre-pregnancy BMI, whether the patient identifies as non-Hispanic Black, whether she identifies as Hispanic, whether she has had a prior vaginal delivery, whether she has had a prior successful VBAC, and whether her earlier cesarean's indication tends to recur (such as failure to progress) — combine into a single weighted score, which the logistic function converts into a predicted percentage chance of a successful vaginal birth.
It's worth being direct about a genuine limitation here. The original 2007 model includes race and ethnicity as predictors, because in the derivation cohort, non-Hispanic Black and Hispanic identity were statistically associated with lower observed VBAC success. That choice has become a real point of clinical debate: critics have argued that building race and ethnicity into the formula can lower a Black or Hispanic patient's predicted success rate and, in turn, shape how strongly a trial of labor gets recommended to her, potentially widening disparities in access to VBAC counseling. In 2021, Grobman and colleagues published a revised calculator in the American Journal of Obstetrics and Gynecology that replaced the race and ethnicity terms with other clinical variables specifically to address that concern.
This calculator uses the original 2007 version rather than the 2021 revision because the revised model's exact coefficients are not published in an open, freely available source the way the 2007 model's are — that's a real gap, not an endorsement of the older approach as unproblematic. This tool exists to support a shared conversation between a patient and her obstetric provider about attempting a trial of labor after cesarean, weighing the predicted probability alongside personal preference and clinical judgment — it isn't meant to make that decision by itself.
- Enter maternal age in years and pre-pregnancy BMI in kg/m².
- Set Non-Hispanic Black and Hispanic to Yes or No, matching how the patient identifies.
- Set Prior vaginal delivery and Prior successful VBAC to Yes or No based on obstetric history.
- Set whether the prior cesarean's indication was recurring, such as failure to progress, to Yes or No.
- Read the logistic linear predictor (w) and the predicted VBAC success percentage.
Worked example — three delivery histories
A 30-year-old with BMI 25, not Black or Hispanic, with one prior vaginal delivery and no prior VBAC or recurring indication, has w = 3.766 − 0.039×30 − 0.060×25 + 0.888×1 = 1.984, giving a predicted success probability of e^1.984 ÷ (1+e^1.984) × 100, about 87.9%.
A 35-year-old with BMI 32, identifying as non-Hispanic Black, with a prior successful VBAC but whose earlier cesarean was for a recurring indication like failure to progress, has w = 0.181 and a predicted success probability of about 54.5% — the positive weight from the prior VBAC and the negative weights from BMI and the recurring indication partly offset each other.
A 22-year-old with BMI 22, identifying as Hispanic, with no prior vaginal delivery, prior VBAC, or recurring-indication history, has w = 0.908 and a predicted success probability of about 71.3%, computed from the original 2007 coefficients this calculator implements.
Questions
Is this the newest, most current VBAC calculator available?
No. This implements the original 2007 Grobman MFMU Network model exactly as published. In 2021, Grobman and colleagues published a revised calculator in the American Journal of Obstetrics and Gynecology that replaced the race and ethnicity variables with other clinical factors, partly to address concern that using race and ethnicity in the formula could contribute to disparities in trial-of-labor counseling. That revision's exact coefficients aren't published in an open, freely available source, so this calculator implements the original, fully published 2007 version instead.
Why does the formula include race and ethnicity at all?
The original 2007 model was built from an MFMU Network cohort in which non-Hispanic Black and Hispanic identity were statistically associated with lower observed VBAC success rates, so the regression included them as predictors. This is a genuine point of clinical debate: critics argue that baking race and ethnicity into the formula can lower predicted success for Black and Hispanic patients and affect how strongly a trial of labor gets recommended to them — a central reason the 2021 revision removed those terms.
Should this percentage decide whether to attempt a trial of labor?
No. It's meant to support a conversation between a patient and her obstetric provider about the likelihood of a successful vaginal birth after cesarean, alongside the individual clinical picture, personal preferences, and the risks of both a trial of labor and a repeat cesarean. It isn't a standalone verdict, and the same predicted percentage can reasonably lead different patients to different decisions.
What do the linear predictor and success percentage represent?
The linear predictor, w, is the logistic model's weighted combination of the seven inputs. The logistic function, e^w divided by 1 plus e^w, converts that weighted sum into a probability, which the calculator reports as a percentage. A w near zero corresponds to roughly 50% predicted success; higher values push the percentage up, lower values push it down.
What inputs does the calculator need?
Maternal age, pre-pregnancy BMI, whether the patient identifies as non-Hispanic Black, whether she identifies as Hispanic, whether she has had a prior vaginal delivery, whether she has had a prior successful VBAC, and whether the indication for her earlier cesarean tends to recur, such as failure to progress.
Does a high predicted percentage guarantee a vaginal birth?
No. It's a population-derived probability from the 2007 MFMU Network cohort, not a guarantee for any individual pregnancy. Labor can still turn toward a repeat cesarean for reasons the model doesn't capture, and a lower predicted percentage doesn't rule out a successful VBAC either — it's one input a provider weighs during counseling, not the whole picture.
References
- Grobman WA, et al. — Nomogram for prediction of vaginal birth after cesarean delivery, Obstet Gynecol, 2007;109(4):806
- Grobman WA, et al. — VBAC calculator without race and ethnicity, Am J Obstet Gynecol, 2021;225(6):664
Read this first: This instrument computes a screening figure from population formulas — it is not a diagnosis, and it cannot see the whole picture a clinician can. Use it to inform a conversation, not to replace one.