Parathyroid hormone (PTH) nomograms combine total calcium and intact PTH (iPTH) measurements to classify disorders of calcium homeostasis. Our objective was to determine if using a combination of laboratory, demographic, and clinical parameters improves the accuracy of classification of these disorders. Chart data were collected for 236 patients with physician-ordered iPTH and total calcium tests. Classification was done using 3 approaches: (1) PTH nomogram plotting total calcium and iPTH results against known cases; (2) review of all available chart data ("gold standard"); and (3) multivariate model (classification and regression tree [CART] or logistic regression) using 24 variables. The CART model was developed using the gold standard patient classification and validated using leave-one-out cross-validation. The CART model was significantly (P = .002) more accurate (80.6%) than the PTH nomogram (59.7%) and logistic regression (66.2%) at classifying calcium homeostasis disorders. The CART model used 6 of 24 variables (iPTH, calcium, creatinine, renal transplantation, percentage of females, and urea nitrogen) and had a misclassification error rate of 0.194 (27/139). Classification of disorders of calcium homeostasis based on the PTH nomogram can be improved by using the CART model developed in this study.