The global financial crisis has reignited interest in models of crisis prediction. It has also raised the question of whether financial connectedness—a possible source of systemic risk can serve as an early warning indicator of crises. In this paper, we examine the ability of connectedness in the global network of financial linkages to predict systemic banking crises. Our results indicate that increases in a country’s financial interconnectedness and decreases in its neighbors’ connectedness are associated with a higher probability of banking crises after controlling for macroeconomic fundamentals. The global financial crisis has underscored the role of financial connectedness as a potential source of systemic risk and macroeconomic instability. It has also highlighted the need to better understand whether an increase in connectedness leads to a higher probability of a financial crisis. In this paper, we contribute to the literature on “early warning systems” (EWS) by investigating whether measures of systemic risk, which are based on modeling the global financial system as a network, can serve as early warning indicators and improve the performance of standard crisis prediction models. In doing so, we use two commonly-employed prediction methods – a data mining algorithm and an econometric crisis incidence model.