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New developments in artificial intelligence are now used to produce increasingly sophisticated multimedia false content, such as deepfakes, making false information even more challenging to detect and combat. This creates expansive opportunities to mislead individuals into believing fabricated claims and negatively influence their attitudes and behavior. Therefore, a better understanding of how individuals perceive such content and the variables related to the perceived trustworthiness of deepfakes is needed. In the present study, we developed and validated the Perceived Deepfake Trustworthiness Questionnaire (PDTQ) in English, Italian, and Slovene. This was done in three phases. First, we developed the initial pool of items by reviewing previous studies, generating items via interviews and surveys, and employing artificial intelligence. Second, we shortened and adapted the questionnaire according to experts’ evaluation of content validity and translated the questionnaire into Italian and Slovene. Lastly, we evaluated the psychometric characteristics via a cross-sectional study in three languages (<i>N</i> = 733). The exploratory factor analyses suggested a two-factor solution, with the first factor measuring the perceived trustworthiness of the content and the second measuring the perceived trustworthiness of the presentation. This factorial structure was replicated in confirmatory factor analyses. Moreover, our analyses provided support for PDTQ’s reliability, measurement invariance across all three languages, and its construct and incremental validity. 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