This study presents a comprehensive bibliometric analysis of 132 articles from the Scopus database, specifically examining the forecasting of gold prices. It explores publication trends, prominent journals, influential authors, institutions, and countries in the field. The findings provide valuable insights into the evolution and trends within this domain, guiding researchers in identifying reputable journals for publication. Future research can focus on developing advanced neural network models to accurately capture complex patterns in gold price forecasting, including new architectures, optimization techniques, and additional variables. Integrating sentiment analysis techniques, such as natural language processing and social media analysis, can enhance the incorporation of emotions and market sentiments