GWAS is about computing association power of SNPs with the phenotype of interest. Traditional GWAS tends to look at each SNP independent from other SNPs when measuring association power. However, it has been discovered that there are SNPs that interact with each other to form a phenotypic response (epistasis). Capturing such epistasis interaction is a computational challenge. Random Forest is a machine learning approach that can be used to overcome the difficulty of this problem. This talk describes the strength and weaknesses of using Random Forest for this purpose.