Governments have the potential to improve the civic inclusion of people with intellectual disabilities living in multilingual societies by providing administrative documents in an Easy-to-Read format and in the preferred language of the target audience. This study aims to address the obstacles keeping Swiss and French administrations from successful accessible communication with their English-speaking citizens with disabilities. It assesses the suitability of a free and public neural machine translation system, DeepL, for generating accessible English from Easy-to-Read French source texts. With the goal of increasing the linguistic accessibility of the texts produced by the system, it proposes the introduction of a pre-editing step. A four-part study investigated the issue from three different angles: translation quality, accessibility, and readability. Findings show that pre-editing improves two of the three factors of linguistic accessibility examined, making this type of tool more suitable for producing Easy-to-Read English translations.