Software defects prediction was introduced to support development and maintenance activities and improve the software quality. Reliable defect predictors can significantly optimize the utilization of software projects resources and increase customers confidence in the developed software products. In this paper, three different classifiers (LMT, SMO and J48) are used to study the relations between dependency collected metrics and bugs collected for the software under study. ANT open source software is used in this case study. The selection of this open source was relation to the availability of source code and bug reports. Results varied between the three classifiers and showed J48 to be the best classifier in terms of predicating such correlation between dependency metrics and defects. In general the three classifiers showed that there is a high significant correlation between proposed and evaluated dependency metrics and software defects which showed that they can be used as important early predictors for the software quality in general.