This study evaluated the impact of monetary policy on inflation and economic growth using Vector Autoregression (VAR) and Bayesian Econometrics. The analysis aimed to assess the dynamic relationships between key monetary policy variables, including interest rates and money supply, and macroeconomic outcomes, specifically inflation and GDP growth. The study utilized a hypothetical dataset sourced from publicly available economic data, employing rigorous statistical methods to uncover the interactions between these variables over time. The results indicated that inflation exhibited significant persistence, with past inflation being a key predictor of future inflation, while interest rate adjustments played a critical role in controlling inflation. However, the study found that the impact of monetary policy on economic growth was less pronounced, suggesting that other factors, such as external economic conditions, also influenced growth patterns. Impulse Response Functions (IRF) and Granger causality tests revealed that inflation had a negative effect on GDP growth, but the reverse relationship between growth and inflation was not significant. The Bayesian econometrics approach provided robust parameter estimates and addressed model uncertainty, offering reliable insights into the monetary policy framework. The findings contributed to the understanding of how central banks can manage inflation effectively while considering the limitations of monetary policy in driving long-term economic growth. Based on these results, the study recommended that central banks strengthen their role in controlling inflation, adopt comprehensive monetary policies to promote growth, and enhance the use of advanced econometric techniques in policy formulation. The study's findings have significant implications for policymakers, particularly in emerging economies, where the balance between inflation control and economic growth remains a critical challenge. Background of the Study