Background: Heart failure (HF) patients in intensive care units (ICUs) are rather poorly studied based on varying left ventricular ejection fraction (LVEF) classification. Characteristics and prognosis of patients in ICUs with HF with mildly reduced ejection fraction (HFmrEF), HF with reduced ejection fraction (HFrEF) and HF with preserved ejection fraction (HFpEF) require further clarification. Methods: Data involving clinical information and 4-year follow-up records of HF patients were extracted and integrated from the Medical Information Mart for Intensive Care III (MIMIC-III) database. Tests were carried out to identity differences among these three HF subtypes. Prognostic analyses were performed using Kaplan-Meier survival analysis and Cox proportional-hazards regression modeling. To develop a novel prediction nomogram, forward selection was used as the best-fit model. Prognostic heterogeneity of the subgroups prespecified by stratification factors in pairwise comparisons was presented using forest plots. Results: A total of 4150 patients were enrolled in this study. HFmrEF had the lowest all-cause mortality rate during the 4-year follow-up, which was significantly different from HFrEF and HFpEF (Log-Rank p 0.001). The Cox proportional-hazards regression model also showed that a comparison of HFrEF versus HFmrEF indicated a hazard ratio (HR) of 0.76 (95% CI 0.61–0.94, p = 0.011) and HFrEF versus HFpEF indicated a HR 0.93 (95% CI 0.82–1.07, p = 0.307). Following a multivariable analysis, 13 factors were confirmed as independent. A new nomogram was established and quantified with a concordance index (C-index) of 0.70 (95% CI 0.67–0.73), and the internal validation indicated the accuracy of the model. Stratification factors such as a history of coronary artery bypass grafting (CABG) and comorbidity of chronic obstructive pulmonary disease (COPD) induced prognostic heterogeneity among the three subtypes. Conclusions: Clinical characteristics and prognosis significantly varied among the three subtypes of HF patients in ICUs, with HFmrEF patients achieving the best prognosis. The novel prediction model, tailored for this population, showed a satisfying prediction ability.