Barrett esophagus is the only known precursor to esophageal adenocarcinoma. As definitive diagnosis requires costly endoscopic investigation, we sought to develop a risk prediction model to aid in deciding which patients with gastroesophageal reflux symptoms to refer for endoscopic screening for Barrett esophagus. The study included data from patients with incident nondysplastic Barrett esophagus (n = 285) and endoscopy control patients with esophageal inflammatory changes without Barrett esophagus ("inflammation controls", n = 313). We used two phases of stepwise backwards logistic regression to identify the important predictors for Barrett esophagus in men and women separately: first, including all significant covariates from univariate analyses and then fitting non-significant covariates from univariate analyses to identify those effects detectable only after adjusting for other factors. The final model pooled these predictors and was externally validated for discrimination and calibration using data from a Barrett esophagus study conducted in western Washington State. The final risk model included terms for age, sex, smoking status, body mass index, highest level of education, and frequency of use of acid suppressant medications (area under the ROC curve, 0.70; 95%CI, 0.66-0.74). The model had moderate discrimination in the external dataset (area under the ROC curve, 0.61; 95%CI, 0.56-0.66). The model was well calibrated (Hosmer-Lemeshow test, P=0.75), with predicted probability and observed risk highly correlated. The prediction model performed reasonably well and has the potential to be an effective and useful clinical tool in selecting patients with gastroesophageal reflux symptoms to refer for endoscopic screening for Barrett esophagus.