Repeated 24-hour urine collections are used to evaluate risk factors for recurrence of kidney stones but are costly and burdensome. This study aimed to develop and validate machine learning models to predict 24-hour urine volume from patients’ self-reported beverage intake and classify compliance with guidelines for preventing kidney stone recurrence.