This master thesis is written in cooperation with the startup studio trive from Vienna. Startup studios produce startups systematically with a core team, to gain startup equity in exchange for time, effort, and experience.In order to increase the profitability and survival rate of the startups they produce, startup studios want to standardize as many processes related to the creation of startups as possible.A crucial point in the development of a startup is to show traction for the venture after a certain period of time, which means that quantitative evidence for the success of a venture is available. If this is the case, a startup has found product-market fit. If this does not happen after 12-18 months, doubts about the success of the venture arise and it is at increased risk of failing. To avoid this, the goal of this master thesis was to develop a model that allows trive to achieve product-market fit regardless of the industry the startup is in.The work includes a detailed discussion of the term product-market fit, which indicates that a certain product satisfies the needs of a market that can be served in a profitable way. In addition, the two main components of the term were each elaborated before discussing methods of creating the "fit" between them. Startup studios can use plan-driven methods or agile methods, whereby agile methods are particularly suitable in the face of uncertainty.From the approaches described in the literature a model was then developed, which was then subjected to a review by expert interviews. Through the interviews, the model could be examined from a practical point of view, and standardizable and non-standardizable process steps could be identified. Through this, a first draft of a model for achieving product-market fit for startup studio-born startups could be elaborated. This first draft of the elaborated model comprises an iterative, customer-centric, and hypothesis-driven approach including all relevant process steps and tasks, which could meet the requirements of a startup studio by basing the model operatively on a Scrum-like procedure.