This quantitative-qualitative analytical research aimed at investigating the effect of integrating project-based teaching methodology into teaching machine translation on students’ performance. Data was collected from the graduate students in the College of Languages and Translation, at Imam Muhammad Ibn Saud Islamic University, Riyadh, Saudi Arabia. Quantitative data instruments included a Likert scale questionnaire, students’ exam results, and students’ assignments. Qualitative data was gathered using two groups, of 20 students each, from the same research population to explore the effectiveness of project-based teaching methodology. The first group of participants was taught for one semester using traditional teaching methods that depended on direct instruction and memorization of information while the second group of participants was involved in creative projects about various topics on machine translation. Content analysis was conducted to evaluate the participants’ projects. A comparison of the two groups’ final exam results and assignments was made to provide statistical evidence regarding the impact of project-based teaching approach on students’ performance. The discussions of this research include topics on theories and systems of machine translation, the concepts of localization and hybridization, project-based teaching methodologies, and educational technology. The recommendations emphasize the importance of adopting brain-based strategies such as project-based techniques in teaching machine translation, providing professional development programs on using cognitive teaching approaches, and equipping translation laboratories with most recent technologies. The significance of this research derives from being a contribution in three specific areas: integrating education research into teaching machine translation to motivate students to improve their performance; employing educational technology to bridge the gap between theories and practice of machine translation; providing an implementation of creative teaching in machine translation through presenting students’ creative projects. The integrative teaching model, which the researcher presented in this research, is a new approach for solving students’ problems in machine translation.