In this paper we present a set of experiments performing machine translation related to low-resourced Arabic dialects in addition to a zero-resourced dialect (Berber). For this, we extended the parallel PADIC corpus by adding the Berber dialect corpus and translating manually more than 6000 Arabic sentences. We applied both Rule-based Machine Translation (RBMT) and Statistical Machine Translation (SMT) with and without a transliteration process. The average overall BLEU score is 42.68% with RBMT and 61.94% with SMT.