Six electronic health record algorithms detected statin intolerance in 5.09% of patients prescribed statins for primary cardiovascular prevention, with the Singapore SIMs-B algorithm achieving 92.95% sensitivity while Japan's SAMT algorithm reached 99.13% specificity. The study validated these automated detection systems against clinical reference standards in real-world general practice settings. This research addresses a critical gap in cardiovascular care, where statin intolerance affects millions but often goes unrecognized in routine practice. The 5.09% prevalence sits at the lower end of the typically reported 5-15% range, potentially reflecting underdetection in electronic systems versus clinical reality. For patients and providers, these algorithms could serve as early warning systems to prompt closer monitoring or alternative lipid management strategies. However, the variable performance metrics—with no single algorithm excelling across all measures—underscore the complexity of diagnosing statin intolerance. The authors appropriately caution that these tools should supplement rather than replace clinical judgment. As a preprint awaiting peer review, these findings require validation before clinical implementation. This represents incremental progress toward personalized statin therapy, though the modest accuracy scores suggest current algorithms need refinement before widespread adoption.