A Fuzzy Logic Framework for Forecasting Gold Prices in Complex Global Environment is a research study authored by Malek Khalef Albuzirat, Moath Ali Alshorman, and Asia Khalaf Albzeirat. The study proposes a fuzzy logic–based forecasting framework to predict gold prices under conditions of economic and geopolitical uncertainty. The model incorporates major influencing factors, including global economic risk, financial market volatility, energy price shocks, and geopolitical tensions, to generate interval-based price forecasts rather than single-point estimates. Using a reference gold price of USD 4,000 per ounce at the end of 2025, the framework evaluates three market scenarios—stable, developing-risk, and high-risk conditions—forecasting price ranges of USD 4,050–4,100, USD 4,150–4,250, and USD 4,400–4,550 per ounce, respectively, for early 2026. The results indicate that geopolitical risk exerts the greatest influence on gold price movements and demonstrate that fuzzy logic provides a robust approach for modeling uncertainty and supporting investment and policy decision-making in highly volatile global markets. Keywords: Gold, Fuzzy logic, Gold price forecasting, Geopolitical risk, Market volatility, Economic uncertainty, Financial forecasting, Decision support, Intelligent modeling.