Clinicians’ prognoses of dying patients may be improved by involving a multidisciplinary team (MDT). However, the process of MDT prognostic decision-making is not well understood. This thesis investigated how members of hospice MDTs formulate and make prognostic determinations. Three studies were conducted, applying a mixed methods research approach to address the study aims. A scoping review revealed that prognoses were primarily made by doctors and nurses and were often subsumed in discussions of other aspects of care. The review showed a prominent lack of research from specialist palliative care settings. Furthermore, there was an evidence gap regarding quantitative studies investigating MDT decision-making and how MDT members formulate prognoses. For this reason, an online Randomised Controlled Trial study evaluating how prognostic “judges” weighed the advice of prognostic “advisors” (including algorithmic advisors) was conducted. The study found that palliative care MDT members (regardless of professional background and experience) integrated prognostic advice more when they perceived it to come from a prognostic algorithm rather than from another clinician with a different profession. To understand how prognoses were formulated, a conversation analytic study of hospice MDT meetings was conducted. The study found that prognoses were rarely explicitly discussed during MDT meetings. Prognoses were sometimes discussed when prompted (by an item on the meeting template) or could be mentioned as part of a wider discussion of care. Prognostic time estimates often just included statements that the patient was “dying” or used unspecific timeframes. Specific time estimates rarely occurred. Prognostication was also shown to be an interactionally delicate matter. The use of mixed methodologies provided a greater understanding of prognostic decision-making within hospice MDTs. The findings may be used to guide future research and to inform recommendations for hospice MDT prognostic communication and the discussion about the implementation and feasibility of prognostic algorithms in clinical practice.