Background. Nowadays dissolution of uric acid kidney stones is the first line treatment according to existing clinical guidelines. Besides dual-energy CT, which is costly, there is no non-invasive tool to predict uric acid stone composition.Aim. To develop a new tool for uric acid stones prediction which will improve patient selection for oral stone dissolution therapy.Materials and methods. We retrospectively analyzed treatment results of 189 patients which were distributed to two groups: with pure uric acid stones - 59 patients and with other composition - 130 patients. Demographic data, results of 24 hour urine analysis and CT scans were analyzed.Results. Among above mentioned parameters the following had the highest significance: body mass, body mass index, urine pH and stone density in Hounsfield Units (p<0.01). Product of multiplication of urine pH and CT-stone density called «Urate index» yielded highest AUC (0.96) which permitted with high accuracy diagnose uric acid stones.Conclusion. «Urate-index» is simple to obtain and has high predictive value which might help choosing target population for kidney stone dissolution.