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The CHOKAI and STONE scores are prediction models for ureteral stones. The aims of the present study were to evaluate the diagnostic performance, to examine the optimal cut-off value, and to compare the diagnostic performance of each model.Patients who presented to our emergency department with renal colic were considered for this prospective study. We analyzed the predictive performance of both STONE and CHOKAI scores at their optimal cut-off values, using receiver operating characteristic (ROC) curve and area under the curve (AUC), as well as sensitivity, specificity, positive likelihood ratio (LR+), and negative likelihood ratio (LR−) at the optimal cut-off value.Of the 96 patients who met the inclusion criteria, 79 were definitively diagnosed with ureteral stones. All patients were of Japanese descent. The AUC of the CHOKAI score was 0.971 at an optimal cut-off value of 6, showing a sensitivity of 0.911, specificity of 0.941, LR+ of 15.49, and LR− of 0.094. The AUC of the STONE score was 0.873 at an optimal cut-off value of 8, showing a sensitivity of 0.823, specificity of 0.824, LR+ of 4.662, and LR− of 0.215. The AUC of the CHOKAI score was significantly higher than that of the STONE score (p = 0.010). Of the 73 patients with a CHOKAI score of ≥6, 98.6% had ureteral stones, and of the 68 patients with a STONE score of ≥8, 95.6% had ureteral stones.The simplified CHOKAI score is a useful tool to screen for ureteral stones in patients with renal colic.