This study investigates how translation self-efficacy and metacognitive regulation may predict performance in the emerging translation practice of machine translation post-editing (MTPE) by determining the existence and degree of relationships between self-efficacy, metacognitive regulation strategies, and MTPE performance among translation learners in EFL contexts (Chinese speakers who learn English as a foreign language), as well as how they contextualize the condition and state of mind of student translators completing MTPE tasks. Examining these key variables provides theoretical insights into the cognitive processes involved in MTPE and practical implications for developing skilled translation post-editors. This study's conceptual framework is grounded in Bandura's social cognitive theory (SCT), a causal model where self-efficacy directly and indirectly impacts human behavior through mediating processes like outcome expectations, social support, and self-regulation. Multi-item scales consisting of translation self-efficacy and metacognitive regulation as well as an MTPE test were employed to examine the relationships between the predictor variables and the criterion variable. Multiple linear regression was adopted for data analysis to assess the fit of adapted scales and determine how much variance in MTPE performance was accounted for by individual and combination of predictor variables. Results indicated that metacognitive regulation plays a statistically significant role in MTPE performance, even though the overall predictive power of the model remains moderate. The findings provide implications for improving student performance in MTPE training and contribute to the relatively new body of emerging literature regarding translator self-efficacy, metacognitive abilities, and their development.