In this study, a clustering algorithm based on adaptive neural fuzzy inference system (ANFIS) was used for computer-assisted diagnosis of the vertebral column disorder from machine learning databases of UCI (University of California Irvine). Features of pelvic incidence, pelvic tilt and lumbar lordosis angle given in this dataset was applied to the inputs of the algorithm. The performance of algorithm was evaluated using mean square error and regression coefficient criteria to discriminate patients with vertebral column disease from healthy subjects. As a result, the classification performance of 90.82% was obtained by using the generated model of ANFIS.