We developed a prediction model to distinguish between malignant and nonmalignant lymphadenopathies. We first analyzed clinical features of 222 patients with lymphadenopathy (161 malignant and 61 nonmalignant) in the derivation group. Through logistic regression analysis we identified 6 covariates that independently predict malignancy: age (X1), abdominal lymphadenopathy (X2), lymphadenopathy of the other sites (X3), number of enlarged lymph node regions (X4), absence of fever (X5), and largest lymph node size (X6). We determined the formula as follows: predictive score=-2.3+x1+2.8x2+1.3x3+1.6x4-2.2x5+1.8x6.A higher score correlated with increased likelihood of malignancy. With the cutoff value of 0.4, the sensitivity and specificity of the model were 91.9% and 77.0%, respectively. The validation study using 117 cases (82 malignant and 35 nonmalignant) yielded 90.2% sensitivity and 68.6% specificity. A maximum lymph node size of less than 2.0 cm on systemic computed tomography (CT) scanning indicated a low probability of malignant lymphadenopathy. In this model, 4 of the 6 covariates were obtained by CT scanning, which strongly indicates the usefulness of initial evaluation with systemic CT scanning in the detection of malignant lymphadenopathy.