In this chapter, we introduce a simple and intuitive principle for estimating the model of independent component analysis (ICA). This is based on maximization of nongaussianity. Nongaussianity is actually of paramount importance in ICA estimation. Without nongaussianity the estimation is not possible at all, as shown in Section 7.5. Therefore, it is not surprising that nongaussianity could be used as a leading principle in ICA estimation.