["Geriatrics &Gerontology International, Volume 26, Issue 8, August 2026. ", "\nA novel logistic regression model leverages age, sex, and mFI‐v10 data to predict clinical frailty. By translating claims data, this scalable framework achieves 76.5% predictive accuracy, enabling healthcare systems to effectively identify and prioritize high‐risk patients using existing electronic medical record infrastructures.\n\nABSTRACT\n\nBackground\nWhile the Clinical Frailty Scale (CFS) is intuitive for clinical use, its reliance on clinician interviews limits its feasibility for large‐scale population monitoring. The claims‐based multimorbidity frailty index‐version 10 (mFI‐v10) is highly scalable but has not been directly linked to the CFS standard. This study aimed to develop a model to translate mFI‐v10 scores into clinically interpretable CFS categories.\n\n\nMethods\nIn this study, 1038 individuals aged ≥ 65 years were recruited from a tertiary medical center between January 2020 and December 2021. They underwent assessments including the CFS, cognitive function, mood, physical health, and quality of life. The mFI‐v10 score was calculated from electronic medical records. Logistic regression with 5‐fold cross‐validation was used to develop a prediction model for moderate‐to‐severe frailty, adjusting for age and sex. Model performance was evaluated using accuracy, sensitivity, specificity, precision, the F1‐score, and the area under the receiver operating characteristic curve (AUC‐ROC).\n\n\nResults\nAmong the 1038 participants, 331 (32%) had moderate‐to‐severe frailty. The mean age of the individuals with moderate‐to‐severe frailty was 83.31 years (SD, 7.32), and 40% were male. The mFI‐v10 showed moderate positive correlations with the CFS (ρ = 0.42) and Charlson Comorbidity Index (ρ = 0.57), and a negative correlation with ADL functional independence (ρ = −0.46). The prediction model incorporating mFI‐v10 score, age, and sex demonstrated good discriminative ability with a mean AUC‐ROC of 76.5% (range: 70.7%–82.6%).\n\n\nConclusions\nThe mFI‐v10 is a valid, scalable surrogate for clinical frailty assessment. This translation framework allows efficient population‐level case‐finding, prioritizing high‐risk older adults for targeted clinical intervention.\n\n"]