Funding Acknowledgements Type of funding sources: None. Background Skeletal muscle mass in heart failure (HF) patients is closely related to exercise tolerance and prognosis. Although the dual-energy X-ray absorptiometry (DEXA) method is a standard method for measuring skeletal muscle mass, it is not suitable in a daily clinical setting since it is a costly and hospital-based modality. We recently reported that an equation for appendicular skeletal muscle mass index (ASMI) estimation using anthropometric parameters predicted DEXA-measured ASMI in HF patients with reasonable accuracy. Here, we examined the prognostic impacts of ASMI predicted by the equation (predicted ASMI) in HF patients. Methods Data for 539 patients with HF ( 73 ± 14 years old, 43% female) who received the DEXA method and measurements of calf circumference (CC) and mid-arm circumference (MAC) between August 1, 2015, to August 31, 2020, were used for analyses. DEXA measured-appendicular skeletal muscle (ASM) was calculated as the sum of bone-free lean masses in the arms and legs, and ASMI was defined as ASM/height². Predicted ASMI was calculated as we previously reported: predicted ASMI (kg/m²) = [0.214 × weight (kg) + 0.217 × CC (cm) - 0.189 × MAC (cm) + 1.098 (male = 1, female = -1) + 0.576]/height² (m²). Low ASMI was defined as <7.0 kg/m² in males and <5.4 kg/m² in females, respectively. The primary endpoint was all-cause death. Multiple imputation using chained equations was used for the substitution of missing values. Results The median follow-up period was 1.75 years (interquartile range, 0.96 to 2.37 years), and 73 patients (15%) has died. Kaplan-Meier survival curves showed that patients with low DEXA measured-ASMI and patients with low predicted ASMI had significantly lower survival rates than those with high ASMI (Figure 1). In a multivariate Cox proportional hazard analyses adjusted for age, sex, logarithmic B-type natriuretic peptide, cystatin C based-estimated glomerular filtration rate, and gait speed, DEXA-measured ASMI [hazard ratio (HR), 0.982; 95% confidence interval (CI), 0.967 to 0.988; p<0.001] and predicted ASMI (HR, 0.979; 95% CI, 0.962 to 0.996; p=0.018) were independent predictors of all-cause mortality, respectively. Inclusion of predicted ASMI into the adjustment model improved the accuracy of prediction of the mortality after discharge [continuous net reclassification improvement, 0.338, p<0.01; integrated discrimination improvement, 0.020, p < 0.05] (Figure 2). Conclusions ASMI estimated by an equation using CC and MAC predicted the prognosis of HF patients at a similar level of accuracy to DEXA-measured ASMI, and it can be applied to the assessment of skeletal muscle mass in a daily clinical setting and in large population-based studies.