Inflation is one of the most important challenges facing Iran's economy, and understanding its driving factors is essential for effective economic policymaking. This study employs a structural interpretive modeling (ISM) approach, drawing on library research and prior studies, to analyze the causal relationships among key variables impacting the inflation rate, including oil revenue, tax revenue, government budget deficit, liquidity growth, exchange rate, output gap, loan-to-deposit ratio, and bank interest rate. The main research questions focus on the role of liquidity growth in inflation and the systemic positions of interest rate and inflation rate. The model's results indicate that oil revenue, as an exogenous variable, affects liquidity growth through its impact on government revenues; liquidity growth, in turn, influences the exchange rate, inflation rate, and bank interest rate. Furthermore, the interest rate and inflation rate occupy the same systemic level and maintain a bidirectional relationship. The findings highlight the importance of managing the budget deficit and liquidity growth to achieve price stability and improve the efficiency of the banking system.