Computerized Adaptive Testing (CAT) is a beneficial test technique that decreases the number of items that need to be administered by taking items in accordance with individuals' own ability levels. After the CAT applications were constructed based on the unidimensional Item Response Theory (IRT), Multidimensional CAT (MCAT) applications have gained momentum with the improvement of multidimensional IRT (MIRT) models in recent years. Researchers often benefit from simulation studies in order to design the final adaptive testing application and to test the effectiveness of adaptive testing applications they developed with different methods. Recently, R has become one of the most widely used programming languages in Monte Carlo Simulation studies since it is a free and open-source software. The aims of this study are to present the MCAT simulation process step by step in the R environment, to examine the effects of the conditions that researchers can handle during the simulation process according to two different dimensional models, and to examine the effect of treating multidimensional structures as unidimensional structures on simulation results. In this direction, datasets generated in accordance with within-item dimensionality and between-item dimensionality models, MCAT simulation studies were constructed with different customizations, and MCAT simulation results were compared with unidimensional CAT simulation results. All commands required for each simulation example were explained and results were shared for each condition.