This paper presents a study about ambiguous French prepositions, stressing out their roles as dependencies introducers, in order to derive some translation heuristics into English, based on a FrenchEnglish set of parallel texts. These heuristics are formulated out of statistical observations and use some up-to-date results in Machine Translation (MT). Their originality mostly relies upon two items: (1) The importance given to syntax and dependency relations, along with lexicons, the latter being well browsed by the present literature in the domain (2) The existence of intrinsic semantics in prepositions, something rather discarded in NLP literature devoted to statistical MT, that tends to point at the most appropriate translation. An experiment has been run on corpora in both languages, using a dependency parser in the source language, and results looked to be encouraging for a “step by step approach” for MT improvement.