Recently, many applications require data to be integrated from different data sources in order to satisfy user queries. Therefore, it was the emergence of using virtual data integration. Data fusion in the virtual data integration environment starts after detecting and clustering duplicated records from the different integrated data sources. It refers to the process of selecting or fusing attribute values from the clustered duplicates into a single record representing the real world object. In this paper, a statistical technique for data fusion is introduced based on some probabilistic scores from both data sources and clustered duplicates.