Esophageal adenocarcinoma has poor 5-year survival rates. Increased survivalmight be achieved with earlier treatment, but requires earlier identification of the precursor, Barrett's esophagus. Population screening is not cost effective, this may be improved by targeted screening directed at individuals more likely to have Barrett's esophagus. To develop a risk prediction tool for Barrett's esophagus, this study compared individuals with Barrett's esophagus against population controls. Participants completed a questionnaire comprising 35 questions addressing medical history, symptom history, lifestyle factors, anthropomorphic measures, and demographic details. Statistical analysis addressed differences between cases and controls, and entailed initial variable selection, checking of model assumptions, and establishing calibration and discrimination. The area under the curve (AUC) was used to assess overall accuracy. One hundred and twenty individuals with Barrett's esophagus and 235 population controls completed the questionnaire. Significant differences were identified for age, gender, reflux history, family reflux history, history of hypertension, alcoholic drinks per week, and body mass index. These were used to develop a risk prediction model. The AUC was 0.82 (95% CI 0.78-0.87). Good calibration between predicted and observed risk was noted (Hosmer-Lemeshow test P = 0.67). At the point minimizing false positives and false negatives, the model achieved a sensitivity of 84.96% and a specificity of 66%. A well-calibrated risk prediction model with good discrimination has been developed to identify patients with Barrett's esophagus. The model needs to be externally validated before consideration for clinical practice.