During the lifetime of a nuclear reactor, the core and its surrounding materials will experience a wide range of temperatures which significantly impact the probabilities of certain neutron interactions (fission, capture, scattering, etc.). These probabilities are referred to in the nuclear community as ‘cross sections’ and are used as inputs for computer simulations. In the case of advanced reactor designs such as the gas-cooled reactors, there is a large axial temperature variation in the fuel pins from the fuel centerline. In the case of coupled neutronic-thermal-hydraulic codes, the temperatures are not always known a priori. A large amount of cross section data is necessary to encompass the entire energy and temperature range a neutron may experience in a problem. In recent years, methods have been developed to reduce data storage by only storing zero-temperature resolved-resonance cross section data and then using functional expansions to attain the cross section at the desired temperature ‘on-the-fly’ during the random walk of the neutron in the Monte Carlo process. These methods are not applicable at low energies because of the complicated nature of chemical and binding effects. This work focuses on developing methods to temperature-correct the thermal scattering cross section ‘on-the-fly’ for incorporation into current online Monte Carlo methods.