The accurate prediction of inflation rates holds critical significance for both policymakers and economic agents. It is imperative to comprehend the limitations and strengths inherent in different models and information sets used to forecast inflation across varying time horizons. This study seeks to enhance the existing literature on Brazilian inflation forecasting by assessing the predictive efficacy of predictors robust to structural breaks, with a particular emphasis on the methodology introduced by \cite{martinez2022smooth}. The findings of this study indicate that robust predictors exhibit notably superior performance during periods of instability and structural change. In the Brazilian context, these predictors outperform expert forecasts specifically during the COVID-19 pandemic period, as indicated by the Focus Survey. However, it is noteworthy that in the immediately preceding period, these models do not outperform the aforementioned survey.
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