This study investigates the impact of oil price fluctuations on inflation in Pakistan, focusing specifically on asymmetric effects. Employing the Nonlinear Autoregressive Distributed Lag (NARDL) model, it examines how oil price increases and decreases influence inflation differently. Using secondary annual data from the Pakistan Bureau of Statistics and the State Bank of Pakistan, the study considers the Consumer Price Index (CPI) as the dependent variable, while independent variables include domestic oil prices (LOP), exchange rate (LEXH), interest rate (LINTR), and unemployment rate (LUNEMP). The Augmented Dickey-Fuller (ADF) test assesses stationarity, revealing mixed integration orders (I(0) and I(1)), which justifies the application of the Autoregressive Distributed Lag (ARDL) model to explore both long-run and short-run relationships. The ARDL bounds test confirms the presence of a long-run relationship among the variables. Results indicate that oil prices significantly affect inflation, with past oil prices exhibiting a persistent impact. The NARDL model highlights asymmetry, showing that oil price increases (LOP_POS) exert a stronger positive effect on inflation than decreases (LOP_NEG). Exchange rate fluctuations display mixed effects, with lagged depreciation negatively influencing inflation, while interest rates and unemployment rates do not demonstrate statistically significant longrun effects. Diagnostic tests, including normality, serial correlation (Breusch-Godfrey LM test), and heteroskedasticity (Harvey, White, and Glejser tests), confirm the model's validity. These findings offer key insights for policymakers, underscoring the necessity of targeted interventions in response to oil price shocks. Given the asymmetric effects, monetary authorities should implement differentiated strategies for oil price increases and decreases to manage inflation effectively. Additionally, exchange rate stability plays a crucial role in mitigating inflationary pressures. Future research may expand on this study by incorporating additional macroeconomic variables or employing alternative econometric approaches to enhance inflation modeling in developing economies like Pakistan.