The majority of urinary stones in children are composed of calcium oxalate. To investigate the interaction between urinary calcium, oxalate, and citrate as major risk factors for calcium stones formation, their 24-h urinary excretion was determined in 30 children with urolithiasis and 15 normal healthy children. The cutoff points between children with urolithiasis and healthy children, accuracy, sensitivity, and specificity for each risk factor alone as well as for all three taken together were determined. OneR and J4.8 classifiers as parts of the larger data mining software Weka, based on machine learning algorithms, were used for the determination of the cutoff points for differentiation of the children. The decision tree based on J4.8 classifier analysis of all three risk factors together proved to be the best for differentiating stone formers from normal children. In comparison to the accuracy of the differentiation after calcium and oxalate of 80% and 75.6%, respectively, the decision tree showed an accuracy of 97.8%. Even when its stability was tested by the leave-one-out cross-validation procedure, the accuracy remained at a very acceptable percentage of 93.2% correctly classified patients. J4.8 classifier analysis gave a look inside urinary calcium, oxalate, and citrate interaction. Urinary calcium excretion was shown as the most informative in discrimination of the children with urolithiasis from healthy children. However, it was shown that oxalate and citrate excretions might influence the stone formation in a subpopulation of the stone formers. In patients with low urinary calcium, a major role in lithogenesis belongs to oxalate, in some of them alone and in others in conjunction with citrate. Decreased urinary citrate excretion in the presence of increased oxalate excretion may lead to stone formation.