In previous research, we showed that risk factors have a significant negative effect on reliability (e.g., failure occurrence). In this research, we show that it is feasible to predict risk (i.e., the probability that risk factors are related to discrepancy reports occurring on a software release). This is an important advance over the previous research because discrepancy reports are available in the requirements phase -- when the cost and labor required to correct faults is low, whereas failure data only becomes available in the test phase -- when the cost and labor required to correct faults is high. Although using historical failure data to drive traditional software reliability models would produce greater prediction accuracy, the opportunity to provide early prediction of reliability, using risk factors, outweighs this advantage.