The article describes the process for establishing a collaborative research agenda to address gaps in understanding of the diagnosis, treatment management of facial palsy. A Delphi technique was used in order to establish a facial palsy research agenda. In round 1, focus groups of patients and professionals were held to answer “What are the research priorities for facial palsy?”, in addition to an online and postal survey. The ‘long list’ of research topics generated was distributed to those who registered to take part in the study, requesting that they ranked how important they believed each research topic to be using a Likert scale from 1 (very important) to 5 (very unimportant). Any questions which failed to reach a rating of important or very important from 70% of respondents were removed, leaving 42 research priorities for the final round. In round 3, the consensus list was again distributed to those who agreed to take part (62 patients or carers and 16 healthcare professionals or researchers) in the study, and they were asked which topics should be addressed in the next five years. Interestingly, seven out of the top ten research priorities for the two subgroups (patient and HCP) were shared, revealing a high level of consensus amongst stakeholders about the questions requiring urgent attention. High ranking topics included “How can synkinesis be prevented and treated?”, “What is the best protocol for clinically managing facial palsy?”, “What is the best way to manage eye discomfort (e.g. dry eyes and watering) in those with facial palsy?”, “What is the psychosocial impact of living with facial palsy, both in adults and children?”, “What is the existing knowledge of frontline healthcare staff (e.g. GPs) in dealing with facial palsy and how can this be improved?”, and “What influence does access / no access to treatment have on patient’s functional and psychological outcomes?” The authors cite a number of limitations to the Delphi study, that participants required email access and computer skills, researcher bias may have come in when the qualitative data from the open response round was analysed and grouped into similar research questions, and that some of these research questions may already be being addressed, albeit the research outcomes not known.