High-grade tumor budding is an adverse prognostic factor for submucosal invasive (T1) colorectal cancer used to predict the risk for lymph node metastasis in endoscopically resected specimens. Cytokeratin immunohistochemistry is a potential option for evaluating tumor budding. The optimal cut-off value between low- and high-grade budding has not yet been determined, however, and the high inter-observer variability in selecting budding foci remains problematic. We explored the optimal cut-off value for predicting lymph node metastasis using cytokeratin immunohistochemistry, and developed a novel computer-assisted semiautomatic quantification method to reduce inter-observer variability. A retrospective single-institution study of 463 T1 colorectal cancer cases was conducted. Cases were split into derivation and validation datasets. Tumor budding foci were counted manually and semiautomatically using Image J software on cytokeratin immunohistochemistry-stained specimens. We determined the cut-off values and compared inter-observer variability among pathologists between the two methods. Univariate and multivariate analyses of the derivation dataset were performed to select the risk factors for lymph node metastasis. Predictive simulation for the validation dataset was conducted. The optimal cut-off values for the manual and semiautomatic methods were ≥10 and ≥12, respectively. For both methods, multivariate analyses revealed that venous invasion, lymphatic invasion, and high-grade tumor budding were independent risk factors for lymph node metastasis. The semiautomatic method provided significantly better inter-observer agreement. The predictive and observed lymph node metastasis frequencies were highly correlated in the validation dataset.