This research aims to develop an Auto-Regressive Integrated Moving Average (ARIMA) model for forecasting the National Consumer Price Index (NCPI) in Nepal, using annual data from 1972/73 to 2022/23. The study employs the Box-Jenkins technique and E-Views statistical software to identify the most suitable ARIMA model. The ARIMA (1, 2, 8) model is selected as the best fit, validated through diagnostic tests that show white noise characteristics in the residuals. The model's accuracy is further confirmed by low Root Mean Squared Error (RMSE) and Theil Inequality Coefficient values. The forecast suggests a rapid increase in the NCPI in the coming years, with a projected value of around 200 points by 2028. This research provides valuable insights for policymakers and stakeholders, aiding in informed decision-making to sustain economic stability in Nepal.This research aims to develop an Auto-Regressive Integrated Moving Average (ARIMA) model for forecasting the National Consumer Price Index (NCPI) in Nepal, using annual data from 1972/73 to 2022/23. The study employs the Box-Jenkins technique and E-Views statistical software to identify the most suitable ARIMA model. The ARIMA (1, 2, 8) model is selected as the best fit, validated through diagnostic tests that show white noise characteristics in the residuals. The model's accuracy is further confirmed by low Root Mean Squared Error (RMSE) and Theil Inequality Coefficient values. The forecast suggests a rapid increase in the NCPI in the coming years, with a projected value of around 200 points by 2028. This research provides valuable insights for policymakers and stakeholders, aiding in informed decision-making to sustain economic stability in Nepal.