Various methods of nonlinearity estimation have been proposed. The Gaussian Noise model(GN model) is one of the most important methods which estimate the nonlinear noise in frequency domain. One of the defects of the GN model is that this model assumes that the signal transmitted into the transmission fiber is Gaussian distributed. Many signals don’t meet this assumption for different baud rates, modulation formats and pulse shapes. The Gaussian distribution of the signal can't be visualized before the proposing of Gaussian Fitting Error.<p> </p> In this paper, we simulate different modulation formats(QPSK and 16QAM), different channel space (37.5 GHz and 50GHz), different pulse shapes (RZ and NRZ) and different fiber types (SMF and NZDSF). The histograms under different conditions will be used to calculate the Gaussian Fitting Error. Then proper amount of pre-dispersion is added before transmission to lower the Gaussian Fitting Error.<p> </p> The results show that without pre-dispersion, the analytical simulation approximation for the GN-Model nonlinear interference power spectral density is obviously not precise under the given conditions. Different modulation formats also affect the model’s accuracy. The model goes well with different modulation format in Nyquist systems. While for non-Nyquist systems, the model is applicable only under certain conditions.<p> </p> Our results suggest that the GN model is reliable when the Gaussian Fitting Error of the signal is low enough. The amount of pre-dispersion is not fixed. The Gaussian Fitting Error should be used to judge the precision of the amount of pre-dispersion to get the optimal result.