Abstract: In silico modeling of oral drug absorption has received widespread attention over the past few years. These models require a number of input parameters and the accurate prediction is often limited by the lack and/or inappropriate selection of reliable input data. The objective of this study was to explore the predictive properties of GastroPlus^TM simulation technology using BCS class II drug nimesulide as a model compound. Model sensitivity to the input data and accuracy to predict drug pharmacokinetic profile observed in vivo were evaluated by constructing drug specific absorption models by two independent investigators, using different presumptions regarding the key factors that govern nimesulide absorption throughout gastrointestinal tract. The first model was constructed assuming that nimesulide might be a substrate for influx transporters in the intestine. Therefore, the absorption scale factors (ASFs) were adjusted to best match the resultant profile to the in vivo observed data. Experimentally determined intrinsic solubility was used as the input value, and human jejunal permeability was in silico predicted. Drug particle radius was assumed to be 5 microns. The main premise in the second model was that nimesulide is well absorbed after oral administration mainly due to the pH-surfactant induced increase in solubility in the gastrointestinal milieu. Therefore, the ASFs were kept on default GastroPlus^TM values, and input solubility and permeability values were optimized to best match the in vivo data. Drug particle size was 25 microns. The results of the simulations were compared with actual clinical data in order to identify the model yielding the best estimation. The presented data indicate the potential of gastrointestinal simulation technology to predict oral drug absorption. However, in order to obtain meaningful in silico modeling, the necessary input data have to be carefully selected and/or experimentally verified.