It seems an established fact that machine translation has proved its unique utility capacities for global communication. However, evaluating the quality and performance of MT has been and still is a challenge, especially in Persian-English language pairs. Against this background this article examines the current state of research on machine translation evaluation of such pairs. The study reviewed research on evaluating Persian-English MT published since the so-called “neural turn”, searching academic databases using keywords, using a coding framework based on strengths, weaknesses, challenges, and limitations of MT systems, and categorizing information like identified weaknesses and proposed improvements. The results reported in this study include: a) a lack of systematic research due to limited industrial developers in Iran, b) academic disinterest, and c) a need for tailored metrics. Finally, the results will be discussed and suggestions will be provided and areas for future research will be mentioned.

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