Barrett's esophagus is the only known precursor of esophageal adenocarcinoma (EAC). Although endoscopy and biopsy are standard methods for Barrett's esophagus diagnosis, their high cost and risk limit their use as a screening modality. Here, we sought to develop a Barrett's esophagus detection method based on methylation status in cytology samples captured by EsophaCap using a streamlined sensitive technique, methylation on beads (MOB). We conducted a prospective cohort study on 80 patients (52 in the training set; 28 in the test set). We used MOB to extract and bisulfite-convert DNA, followed by quantitative methylation-specific PCR to assess methylation levels of 8 previously selected candidate markers. Lasso regression was applied to establish a prediction model in the training set, which was then tested on the independent test set. In the training set, five of eight candidate methylation biomarkers (p16, HPP1, NELL1, TAC1, and AKAP12) were significantly higher in Barrett's esophagus patients than in controls. We built a four-biomarker-plus-age lasso regression model for Barrett's esophagus diagnosis. The AUC was 0.894, with sensitivity 94.4% [95% confidence interval (CI), 71%-99%] and specificity 62.2% (95% CI, 44.6%-77.3%) in the training set. This model also performed with high accuracy for Barrett's esophagus diagnosis in an independent test set: AUC = 0.929 (P < 0.001; 95% CI, 0.810%-1%), with sensitivity=78.6% (95% CI, 48.8%-94.3%) and specificity = 92.8% (95% CI, 64.1%-99.6%). EsophaCap, in combination with an epigenetic biomarker panel and the MOB method, is a promising, well-tolerated, low-cost esophageal sampling strategy for Barrett's esophagus diagnosis. This approach merits further prospective studies in larger populations.