The COVID-19 pandemic that broke out in 2019 and 2020 brought challenges to translators of different languages. The crisis entailed the introduction of special new terminology for announcing news and communicating in the scientific field about the disease. People all over the globe kept talking about the same single topic at different levels of communication, i.e., daily conversations, scholarly lectures, TV news and programs, medical jargon and so on. Accordingly, there was a need to translate the new terms into different languages and enrich scientific lexicography. This study examines newly coined English terms and their Arabic translation using machine translation systems. A review of linguistic means of localizing these terms is made, and three MT engines are used to translate the newly coined terms into Arabic; Google Translate, Reverso, and Microsoft Translator Bing. It aims to investigate the ability of these MT systems to produce accurate Arabic translations of Covid 19 newly coined terms. The product is compared to the translation of the same terms in Dictionary of COVID 19 Terms by Arab League Educational, Cultural, and Scientific Organization (ALECSO). The results show a difference in accuracy among the three systems. The three MT systems do not provide a product as comprehensive as that rendered by the dictionary. However, they are reliable with a little help from human translators for a better output. It is concluded that the significance of the product rendered by MT systems lies not only in the accuracy but rather in its acceleration during the crisis.