<p>Can artificial intelligence, which has entered every aspect of our lives, be used in the development of measurement tools? In order to answer this question, in this study, a happiness scale was developed through a structured prompt-based process using ChatGPT, under the guidance and evaluation of the researchers. In this study, validity and reliability analyses of this scale were conducted. As a result of the exploratory factor analysis conducted to test the construct validity, it was determined that the seven items in the data collection tool explained 50% of the total variance and the factor loadings of the items ranged between “.60” and “.79”. The goodness-of-fit values obtained as a result of confirmatory factor analysis also showed that the model-data fit for the scale was excellent. It was also determined that criterion scale validity was achieved with two different scales. The Cronbach Alpha internal consistency coefficient of the scale was found to be 0.83. As a result of test-retest reliability analysis, it was found that the scale was stable over time. The findings obtained within the scope of this research show that the developed scale has validity and reliability that can be used to measure the happiness of university students. In this framework, conducting validity and reliability analyses of the happiness scale that ChatGPT assisted will provide valuable contributions to both academic literature and practitioners and will lead to the creation of future psychometric scales.</p>