Objective To investigate the current status of self-care ability in heart failure (HF) patients and construct and validate a predictive model of independent influencing factors, providing a theoretical basis for precision nursing interventions. Methods A total of 80 HF patients admitted to Zhengzhou Central Hospital Affiliated to Zhengzhou University from January 2024 to January 2025 were enrolled. Demographic, clinical, and social support data were collected. Self-care ability was assessed using the European heart failure self-care behaviour scale-9 (EHFScB-9). Multivariable Logistic regression was used to identify predictors of inadequate self-care, and a prediction model was constructed and validated. Results Multivariable Logistic regression analysis showed that the number of people living in the household<3 (OR=2.568), sleep apnea (OR=2.077), hospitalization ≥ 2 times in the past 12 months (OR=2.568), negative perception of the disease (OR=2.440), reduced left ventricular ejection fraction (OR=0.151), and taking ≥ 5 types of medication daily (OR=9.152) are independent risk factors for insufficient self-care ability. The Logistic prediction model was formulated as: P=1/{1+e[0.943×（ household residents ＜ 3） + 0.731 ×（ sleep apnea） +0.675×（ number of hospitalizations in the past 12 months ≥ 2 ） + 0.892×（ negative perception of illness） -1.929×（ reduced left ventricular ejection fraction） +2.214×（ number of medications taken-daily ≥ 5） -8.461]}. The AUC of the model for predicting self-care deficiency was 0.827, and the sensitivity and specificity were 85.74% and 76.83% respectively. Hosmer lemeshow goodness of fit test showed that the prediction model had good calibration ability (χ2=2.274, P=0.796). Conclusion Multidimensional deficiencies significantly impair self-care ability in HF patients. The validated prediction model effectively identifies high-risk individuals, enabling targeted interventions to optimize HF management.