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Abdominal aortic calcification (AAC), a recognized measure of advanced vascular disease, is associated with higher cardiovascular risk and poorer long‐term prognosis. AAC can be assessed on dual‐energy X‐ray absorptiometry (DXA)‐derived lateral spine images used for vertebral fracture assessment at the time of bone density screening using a validated 24‐point scoring method (AAC‐24). Previous studies have identified robust associations between AAC‐24 score, incident falls, and fractures. However, a major limitation of manual AAC assessment is that it requires a trained expert. Hence, we have developed an automated machine‐learning algorithm for assessing AAC‐24 scores (ML‐AAC24). In this prospective study, we evaluated the association between ML‐AAC24 and long‐term incident falls and fractures in 1023 community‐dwelling older women (mean age, 75 ± 3 years) from the Perth …