Forecasting is an integral part of supply chain management. Accurate forecasts lead to the effective utilization of inventory. The accuracy of forecasts depends not only on how the forecasts are generated with the help of system statistical models, but also on how the human judgments incorporate the contextual information outside the system. The latter part is called judgmental forecasting, where the forecaster brings their experience, knowledge, and external information to the system to produce accurate forecasts. This study presents a comprehensive review of the literature on judgmental forecasting from 1976 to 2025 (August). This is the first study to present fifty years of the review of judgmental forecasting to capture how this research field started and the status of its integration with the statistical system in the present. Drawing on 242 peer-reviewed journal papers from the Scopus database following the PRISMA framework, we conducted performance analysis and science mapping using tools like R Biblioshiny and VOSviewer. The future research directions are also discussed at the end of this article to help research scholars and industry practitioners delve into this niche research area to study and explore its practices.