Milk and beef production is crucial to ensure a cost-effective and sustainable food supply. As the demand for agricultural products increases, making informed decisions are critical. Discrete event simulation, a suitable tool for modeling many complex systems with random variability, offers substantial advantages compared with traditional analytical models. We developed a discrete event simulation model for a dairy herd. The model is shown useful for studying various culling strategies based on disease or reproductive performance. We perform a preliminary validation of the model by comparing steady state behavior to analytical results from a Markov chain model and literature. Our findings demonstrate that twin calving does not significantly affect herd performance. We advocate the use of discrete event simulation integrated in smart management tools, emphasizing its usefulness in decision-making on dairy farms. In future research, we are exploring additional factors such as abortion, mortality, and time variable periods for state variables.