The Consumer Price Index (CPI) is an essential macroeconomic indicator for economic policy. In the context of global economic volatility, this study uses an ARIMA(1,2,0) model to analyze the historical dynamics of the CPI and generate accurate forecasts. The data used cover the period 2000-2024, adjusted after confirming a postdollarization structural break. The results of the Augmented Dickey-Fuller (ADF) test confirmed that the transformed series with a second-order differencing (d=2) is stationary. The selected ARIMA model, based on the Akaike Information Criterion (AIC) and the Bayesian Information Criterion (BIC), demonstrated be robust, with waste that They comply the properties of noise The model was white according to the Ljung-Box and normality tests. Although the individual coefficients were not statistically significant, the model exhibited strong predictive power, underscoring its usefulness for economic planning and informed decision-making in volatile environments.