Abstarct: Foam drilling is one of main branches of underbalanced drilling that has many advantages in many drilling operations. A good knoledg of foam hydraulics and cttings transport using foam is one of the main factors affecting cost, time, and the quality of oil and gas wells. The objective of this study is to investigate of cuttings transport with foam in inclined wellbores using intelligent, statistical and Computational Fluid Dynamics (CFD) methods. The rheological parameters of non-Newtonian bentonite fluids and foam fluid were determined using genetic algorithm. It was identified that genetic algorithm performs better than statistical methods in determining the rheological parameters of drilling fluids. The terminal velocity of spherical solids in Newtonian and non- Newtonian power law fluids was estimated using artificial neural networks (ANNs). The correlation coefficient (R) and root mean square error between the predicted and experimental data were 0.997 and 0.021 for train data respectively. The R and RMS were 0.974 and 0.072 for test data respectively. Besides, artificial neural networks were used to predict the hole cleaning efficiency using foam fluid in horizontal wellbores. The correlation coefficient (R) and RMS between the predicted and experimental data were 0.993 and 0.807 for train data, respectively. The R and RMS were 0.914 and 1.9 for test data, respectively. Hole cleaning efficiency was predicted using a multiple linear regression (MLR). The correlation coefficients (R) between the predicted and experimental data were 0.91 and 0.84 for train and test data respectively. Computational fluid dynamics modeling of fluid (foam) flow and liquid- solid flow (cuttings transport phenomena) in annulus was further conducted using FLUENT commercial software. In foam flow modeling, the effect of various operational parameters on pressure loss such as fluid rheology, foam fluid velocity, foam quality, drillpipe rotation and wellbore eccentricity was considered. Simulation results were compared with the previously published experimental data. The agreement was close with a relative error less than 11% for all models. For cuttings transport modeling, the effect of foam quality, foam velocity, drill pipe rotation, rheological model and wellbore inclination on cuttings transport phenomena in both concentric and eccentric annulus was investigated. The results of CFD using Power law model are in good agreement with experimental results in horizontal annulus respect to Herschel- Bulkly model with relative error less than 8%. This study shows the reliability of the ANN and CFD modeling in replicating the actual physical process.