<p>This study examines the factors influencing the acceptance and use of ChatGPT among pre-service mathematics and science teachers in a teacher education program at a public university in Bahrain. Grounded in the Unified Theory of Acceptance and Use of Technology (UTAUT) and its extension (UTAUT2), the study incorporates performance expectancy, effort expectancy, social influence, facilitating conditions, hedonic motivation, price value, habit, and personal innovativeness to explain behavioral intention and use behavior. Data were collected using a seven-point Likert scale survey administered to 67 pre-service teachers selected through purposeful sampling. The proposed model was analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM). The results reveal that personal innovativeness is the only significant predictor of behavioral intention, while habits significantly predict actual use behavior. In contrast, traditional UTAUT/UTAUT2 constructs including performance expectancy, effort expectancy, social influence, facilitating conditions, hedonic motivation, and price value did not show significant effects. These findings suggest that, in early stages of generative AI adoption, individual disposition and habitual engagement may play a more critical role than perceived usefulness or ease of use. The study contributes to technology acceptance literature by demonstrating the limited explanatory power of traditional UTAUT constructs in the context of emerging AI tools and highlighting the importance of integrating individual difference variables such as personal innovativeness. Practically, the findings highlight the need for teacher education programs to foster innovative mindsets and promote repeated, structured engagement with AI tools to support meaningful integration in STEM education.</p>