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Community-aware metrics through socio-technical developer networks or organizational structures have already been studied in the software bug prediction field. Community smells are also proposed to identify communication and collaboration patterns in developer communities. Prior work reports a statistical association between community smells and code smells identified in software modules. We investigate the contribution of community smells on predicting bug-prone classes and compare their contribution with that of code smell-related information and state-of-the-art process metrics. We conduct our empirical analysis on ten open-source projects with varying sizes, buggy and smelly class ratios. We build seven different bug prediction models to answer three RQs: a baseline model including a state-of-the-art metric set used, three models incorporating a particular metric set, namely community smells …