This chapter introduces a novel translation quality assessment mechanism, which proposes to increase the translatability of English source texts through predictive assessment using machine learning classifiers, before sending the texts for actual translations. The benefits of the pre-editing approach are manifold. First, it can significantly increase the cost-effectiveness of the translation flow, especially for minority languages which often lack adequate staffing of translators and service support in real-life scenarios for migrant communities. Second, translatability enhancement guided by machine learning helps reduce the risks of mistranslations and miscommunications among minorities.