Count data are often modeled using the Poisson model, but this model doesn't work well when the data is underdispersed (variance is less than the mean). This study compared different models to handle underdispersed data. The COM-Poisson model was best for severe underdispersion, while the Double Poisson and Generalized Poisson models performed well for moderate underdispersion with larger sample sizes. No single model fits all situations, so it's important to test multiple models to find the best one.