Treebanks are valuable linguistic resources that include the syntactic\nstructure of a language sentence in addition to POS-tags and morphological\nfeatures. They are mainly utilized in modeling statistical parsers. Although\nthe statistical natural language parser has recently become more accurate for\nlanguages such as English, those for the Arabic language still have low\naccuracy. The purpose of this paper is to construct a new Arabic dependency\ntreebank based on the traditional Arabic grammatical theory and the\ncharacteristics of the Arabic language, to investigate their effects on the\naccuracy of statistical parsers. The proposed Arabic dependency treebank,\ncalled I3rab, contrasts with existing Arabic dependency treebanks in two main\nconcepts. The first concept is the approach of determining the main word of the\nsentence, and the second concept is the representation of the joined and covert\npronouns. To evaluate I3rab, we compared its performance against a subset of\nPrague Arabic Dependency Treebank that shares a comparable level of details.\nThe conducted experiments show that the percentage improvement reached up to\n7.5% in UAS and 18.8% in LAS.\n