AbstractCalcium oxalate (CaOx) crystal‐induced nephropathies comprise a range of kidney disorders, for which there are no efficient pharmacological treatments. Although CaOx crystallization inhibitors have been suggested as a therapeutic modality already decades ago, limited progress has been made in the discovery of potent molecules with efficacy in animal disease models. Herein, an image‐based machine learning approach to systematically screen chemically modified myo‐inositol hexakisphosphate (IP6) analogues is utilized, which enables the identification of a highly active divalent inositol phosphate molecule. To date, this is the first molecule shown to completely inhibit the crystallization process in the nanomolar range, reduce crystal–cell interactions, thereby preventing CaOx‐induced transcriptomic changes, and decrease renal CaOx deposition and kidney injury in a mouse model of hyperoxaluria. In conclusion, IP6 analogues based on such a scaffold may represent a new treatment option for CaOx nephropathies.