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Transfer-based technique is currently one of the most widely used methods of machine translation. The idea behind this method is to have an intermediate representation that captures the meaning of the original sentence in order to generate the correct translation. In this paper we have explored several features of Arabic pertinent to MT. The hypothesis under investigation and main aims of this paper are to build a robust lexical Machine Translation (MT) system that will accept Arabic source sentences (SL) and generate English sentences as a target language (TL), and to examine how the challenges imposed by this particular language pair are tackled. The paper represents as well a starting point for the future implementation of a successful Arabic MT engine. The conducted experiment proves that our system (AE-TBMT) has scored the highest percentage by 96.6 percent; this means that only three percent of the entire test examples have not been handled correctly, and this result is considered fair if not good, as the other three systems score below that mark.