INTRODUCTION: Early detection of esophageal squamous cell carcinoma (ESCC) significantly improves patient quality of life and outcomes. We aimed to train and validate a predictive algorithm using methylated DNA markers (MDMs) based on encapsulated sponge cell collection device (CCD) samples. METHODS: CCD samples in the training set (n = 120) were taken from 2 medical centers, and those in the validation set (n = 70) were prospectively collected from another medical center. The case group contained a diverse range of esophageal high-grade lesions, including high-grade intraepithelial neoplasia (HGIN), early ESCC, and advanced ESCC. The algorithms were trained on the training set and tested to evaluate diagnostic performance in a prospective validation set. RESULTS: The MDM model was constructed using logistic regression with 2 MDMs (OTOP2 and KCNA3). The areas under the receiver operating characteristic curves were 0.933 (95% confidence interval [CI] 0.881-0.986) and 0.911 (95% CI 0.841-0.981) in the training and validation sets, respectively. The overall sensitivity was 90.0% at a specificity of 91.4% in the training set. The sensitivity was 90.0%, 95.0%, and 90.0% for HGIN, early ESCC, and advanced ESCC in the training set, respectively. The sensitivity and specificity were 87.5% and 86.7% in the validation set, respectively. The areas under the receiver operating characteristic curves for the complex model that included the 2 MDMs and age were 0.961 (95% CI, 0.920-1.000) and 0.940 (95% CI, 0.889-0.990) in the training and validation sets, respectively. DISCUSSION: The assay of MDMs in CCD samples offers a highly accurate method of predicting HGIN/ESCC, thereby providing the potential for early diagnosis and screening for HGIN/ESCC.