Translation technologies, including computer-assisted translation (CAT) tools, translation memory (TM) systems, and machine translation (MT), are increasingly utilized in professional translation workflows and training. However, the effects of these technologies on translators' performance remain inconclusive. This meta-analysis examines the overall impact of translation technologies on translator performance by synthesizing data from 12 experimental studies published between 2000 and 2023. The study investigates the effectiveness of translation technologies compared to traditional translation methods. The findings reveal a significant positive effect size, indicating that translation technologies have the potential to improve translators’ performance relative to purely human translation. The integration of advanced interactive CAT systems and post-editing MT demonstrates larger advancements compared to basic TM match retrieval. Moreover, experienced professional translators derive greater benefits from incorporating technologies than student translators, highlighting the importance of leveraging automation capabilities alongside human expertise. However, the study identifies significant heterogeneity among the studies, influenced by factors such as translation direction. Translators translating into their native language exhibit greater advancements, emphasizing the advantages of technologies that strengthen fluency in the target language.