This study is concerned with establishing the determinants of banks' exposure to risk and with predicting risk in banking. Using the COMPUSTAT data base, prediction rules have been developed for two aspects of risk: systematic risk (risk that is related to covariance with the market portfolio) and residual risk (the aggregate of specific risk and extra-market covariance). For each type of risk, several models have bean estimated: one model employs only measures of the asset and liability characteristics of the bank; a second employs these characteristics and other data taken from annual reports; a third model adds the history of the behavior of the price at the bank's common stock. The central conclusion of the study is that systematic and residual risk in banks can be predicted from predetermined data. Prediction rules estimated in this way can serve a useful function in monitoring bank risk. Further, the predictive significance of each variable serves as a measure of the appropriateness of that variable as an indicator of risk, and hence as a target for regulation.