During the last decade, many papers on defect prediction were published. One still for the most part unresolved issue are cross-project defect predictions. Here, the aim is to predict the defects of a project, with data from other projects. Many approaches were suggested and evaluated in recent years. However, due to the usage of different implementations and data sets, the comparison between the work is a hard task. Within this paper, we present the tool CrossPare. CrossPare is designed to facilitate benchmarks for cross-project defect predictions. The tool already implements many techniques proposed within the current state of the art of cross-project defect predictions. Moreover, the tool is able to load different data sets that are commonly used for the evaluation of techniques and supports all major performance metrics. Through the usage of CrossPare other reseachers can improve the comparability of their results and possibly also reduce their implementation efforts for new cross-project defect prediction techniques by reusing features already offered by CrossPare.