Applications of polytomous IRT models in applied fields (e.g., health, education, psychology) are abound. However, little is known about the impact of the number of categories and sample size requirements for precise parameter recovery. In a simulation study, we investigated the impact of the number of response categories and required sample size for successful parameter recovery and also examined model fit. Our results suggested that sample size requirements of approximately 250 or larger are typically sufficient for reasonable recovery of either person or item parameters (in particular discrimination). Further, we found that in many cases, the conditions of 10 items yielded more favorable results than those conditions when only 5 items were considered. With respect to the number of response categories, results were inconsistent, suggesting more complex recommendations in selecting the number of categories when developing scales. We discuss limitations of the current study, identify future directions, and provide recommendations for applied researchers who engage in scale development.