In this thesis, we introduced a new method which is called the GMN (Gamze, Murat, Nesli¸sah) algorithm. GMN algorithm determines the pre-exponential and activation energy of the curing process. This algorithm include tanh fitting for the measured conversion values via least squares minimization technique and linear fitting for the kinetic parameters. Experimentally determined differential scanning calorimetry (DSC) data sets for an epoxy resin functionalized by single wall carbon nanotubes are used for the verification of the proposed method. In computational part, in order to denote the effectiveness of the new proposed method, the results are also compared with the methods reported in the literature [21]. To sum up, we have shown that the GMN algorithm provides a good match with the experimental data for all kinetic parameters.