The challenges managing advanced heart failure (AHF) are mounting, not least by the presence of multiple coexisting comorbidities, the lack of evidence of clinical benefit in many subsets of AHF, but also surrounding the uncertainty of the both short-term and long-term prognosis. Clinicians are highly variable in their interpretation of clinical data and are prone to considerable bias when it comes to treatment recommendations. This manuscript provides a critical appraisal of the uncertainties as it pertains to the natural history of AHF and management decisions. First, clinical examples are explored to illustrate common errors of judgment due to unrecognized biases. Secondly, a tool is provided that promulgates a structured approach to key data elements in an attempt to create a sound platform for decision-making.