Introduction: Ayurveda offers healthy, harmonious, and long life by its holistic approach. Gout is a form of arthritis caused by excess uric acid in the bloodstream. Gout may be considered as Vatarakta or Vatasonita as per Ayurveda. Even though gout is managed well with conventional medicine, there are a lot of side effects. Ayurvedic treatment is found to be effective in the management of gouty arthritis with very few ill effects. But research works carried out in gout with Ayurvedic medicines are not yet compiled and analyzed. The purpose of this study is to conduct a systematic review of published data and gray literature on Ayurveda management of gout viz-à-viz Vatarakta to establish its safety and clinical effectiveness. Thus, finding more precise estimates of various Ayurveda interventions' effects in the management of gout either as stand-alone or as an add-on to conventional management. Materials and methods: Source for data analysis involves electronic search done from PubMed, Cochrane Library (Cochrane Central Register of Controlled Trials: Issue 6 of 12, June 2018), AYUSH Research Portal (Govt. of India), DHARA, Google Scholar, Ancient Science of Life, Shodhganga@ INFLIBNET, and online clinical trial registers. Manual search in central and departmental libraries of Government Ayurveda College, Trivandrum and IPGT & RA, Gujarat Ayurved University, Jamnagar. There will be no language restrictions. Studies published till date (until March 2019) will be sought. The search will be rerun just before the final analyses, and further studies shall be retrieved for inclusion. Type of studies included randomized controlled trials (RCTs), quasi-experimental trials, single-group clinical trials, comparative clinical trials (CCTs), pragmatic trials, and review papers on Ayurvedic management of Gout, which will all be screened for data analysis. The study selection will follow the preferred reporting items for systematic review and meta-analysis guidelines. Data collection and synthesis: three investigators shall independently screen all citations and abstracts identified by a primary comprehensive search to sort out potentially eligible trials based on inclusion criteria. Data extraction forms for individual study shall be prepared and it may include methods, participant characteristics, intervention, and outcome. When disagreement persists or in case of ambiguity at the time of data extraction, efforts shall be initiated to obtain clarifications directly from authors/coauthors as much as possible. Primary data analysis of both the qualitative and quantitative data will be performed. Heterogeneity among trials will be assessed by inspecting forest plots. If heterogeneity is detected and it is still considered clinically meaningful to combine studies, then a random-effects model (Dersimonian-Laird Model) will be used. In cases where pooled estimates can be obtained, the systematic review will be followed by a meta-analysis (based on the homogeneity of the RCT methodological, appraisal will be done by Cochrane risk-of- bias tool for RCT); others would be presented by narrative synthesis [using Risk of Bias tool in non-randomised clinical trials/non-randomised controlled trials (NRCT)] and shall be represented in tabular and graphical form. The analysis of the systematically collected data shall be analyzed using R software. A sensitivity analysis, to investigate the robustness of the results to the quality components will be done, provided there are sufficient trials. A funnel plot will be utilized to indicate publication bias, heterogeneity of results, or differences in the methodological quality. Timelines: Data collection and analysis: 06 months (from the date of initiation). Journal selection and publication: 03 months (from the date of study completion). Dissemination: The systematic review will be published in a peer-reviewed journal. It will also be disseminated electronically and via print. The review may guide healthcare practices and policy framing in the treatment of gout with Ayurvedic interventions. Trial registration number: PROSPERO 2019: CRD42019131198.