The fault-prone module detection in source code is of im- portance for assurance of software quality. Most of pre- vious conventional fault-prone detection approaches have been based on using software metrics. Such approaches, however, have difficulties in collecting the metrics and con- structing mathematical models based on the metrics. In order to mitigate such difficulties, we propose a novel ap- proach for detecting fault-prone modules using a spam fil- tering technique. Because of the increase of needs for spam e-mail detection, the spam filtering technique has been pro- gressed as a convenient and effective technique for text min- ing. In our approach, fault-prone modules are detected in a way that the source code modules are considered as text files and are applied to the spam filter directly. In order to show the usefulness of our approach, we conducted an experiment using source code repository of a Java based open source development. The result of experiment shows that our approach can classify more than 70% of software modules correctly.