In this article, we develop a nonparametric functional data analysis (NP-FDA) model to forecast the term-structure of Brazil, Russia, India, China and South Africa (BRICS). We use daily data over the period of January 1, 2010 to December 31, 2016. We find that, while it is in general difficult to beat the random-walk model in the shorter-horizons, at longer-runs our proposed NP-FDA approach outperforms not only the random-walk model, but also other popular competitors used in term-structure forecasting literature. In addition, the NP-FDA model is also found to produce economic gains, besides statistical gains, over the random-walk model. Our results have important implications for both policymakers aiming to stabilize the economy, and for optimal portfolio allocation decisions of financial market agents.