Korean financial industry are experiencing rapid environmental changes since Asian financial crisis in late 90’s. Such environmental changes caused an increase of the need for measuring corporate credit risk or default probability Corporate default prediction is not a new theme and many prediction methods have been developed. So far, almost all of the methods are based on accounting informations or qualitative analysis of experts. So, the accuracy of the prediction can be affected by the transparency and the update timing of the accounting informations or the subjectivity of the experts. Recently, to overcome such limits of those prediction methods, some new models which are using investors’ expectations in financial markets are suggested. One of them is the EDF (expected default frequency) model , in which stocks are considered as a call option In this paper, we suggest an EDF model for Korean listed companies and examine whether the EDF model is useful in predicting corporate default in Korea, empirically. And we compare prediction results of the EDF model with other default prediction models The results of empirical tests in this paper show the EDF model is useful in predicting corporate default and in monitoring credit risk changes. And the results of the comparison with other models show that the EDF model provides more powerful and accurate predictive information on corporate default than other prediction models