In this thesis work, it is intended to investigate not only the Extended Kalman Filter (EKF) but to further study the more recent nonlinear Kalman Filters for their application to the nonlinear problem of a continuous stirred tank reactor. The various filters studied in this thesis are:* Extended Kalman Filter (EKF)* Monte Carlo Kalman Filter (MCKF)* Unscented Kalman Filter (UKF) and its various forms and alternate editionsThe study goes on to provide a comparison of the computational and accuracy costs involved in the cases of EKF and UKF.Until recently, the EKF has proven to be a better filter in terms of accuracy for the majority of non-linear cases such as the various cases of a continuous stirred tank reactor. The research work in this thesis also applies these filtering methods to the system dynamics of an exothermic continuous stirred tank reactor. Results obtained in this research corroborate the notion that an Unscented Kalman Filter tends to have a better accuracy than the previously trusted family of Kalman Filters, however after investigating the application of the UKF to the problem studied, it is still not possible to make a strong case for the UKF in general and the conclusion is that the application of this filter remains to be case sensitive.