Purpose: Congestive heart failure (CHF) is a major cause of morbidity and mortality in the population and the societal burden of CHF is likely to escalate in the next decades. Several research groups have developed decision-analytic models to investigate the long-term clinical effectiveness and cost-effectiveness of several interventions. We sought to give an overview on published decision-analytic models and methodological approaches evaluating health technologies in CHF and to derive general recommendations for future comprehensive CHF decision models. Methods: We performed a systematic literature review to identify studies that evaluated diagnostic, therapeutic and disease management procedures for CHF using mathematical decision models. Using a standardized assessment form, information on the study design, methodological framework and data sources were extracted from each publication and systematically reported. Results: We identified 13 studies that used mathematical models to evaluate different pharmaceutical and resynchronization treatment options in CHF. Models evaluating diagnostic work-up or disease management strategies for CHF were not identified. All identified models included clinical and economical outcomes. Modeling approaches comprised mathematical equations and Markov models with a time horizon ranging from one year to lifetime. Treatment effects were modeled by slowing disease progression, which was either represented by New York Heart Association (NYHA) stages or by the number of repeat hospital admissions. The influence of different etiologies of CHF was not considered in the course of the disease in any model. Only one study included quality-adjusted life years as outcome and no study reported external validation results. Conclusion: Well-elaborated decision models are available for CHF treatment but are lacking for diagnostic patient assessment and management and the increasingly implemented disease management programs. Future comprehensive, generic and flexible decision models should link diagnostic and therapeutic options, allow the evaluation of multiple outcomes and quality-of life, integrate different etiopathologies, and be validated with independent data.