Conceptual modeling is by many considered an essential aspect of the software engineering practice, aiding in the documentation and design of complex systems. However, software engineers often abstain from modeling due to the short time frames of software projects and a lack of expertise regarding modeling. The emergence of Large Language models (LLMs) has introduced new possibilities for automating complex tasks, but the integration of LLMs into conceptual modeling tools is fairly unexplored. This thesis aims to bridge this gap by developing a modeling tool that uses ChatGPT and PlantUML, a tool that creates diagrams based on a domain-specific language, to automatically generate the Unified Modeling Language (UML) class diagrams based on natural language domain descriptions. Employing a design science framework, a document survey was conducted for problem explication, followed by semi-structured interviews for requirements elicitation. The tool was developed and evaluated through experiments with experienced modelers. The results showed that the tool sped up diagram creation, but the diagrams sometimes lacked accuracy. These inaccuracies suggest the tool is not suitable for inexperienced modelers in its current state, due to the false sense of security the generated diagrams might foster. Despite these limitations, the tool could still be useful to modelers by decreasing the workload involved in manually creating class diagrams. However, the limited sample size of ten subjects for the experiment raises questions surrounding the reliability and generalizability of the results. This suggests that further research is necessary to explore the tool’s potential in conceptual modeling.