The work which is being presented in this report entitled “Applications of q-Statistics in Big Bang Nucleosynthesis” and submitted in partial fulfilment of the requirements of the degree of Bachelor of Technology in Engineering Physics, Department of Physics, IIT Roorkee. This project describes the use of Tsallis non extensive statistics to calculate the abundances of light elements during big bang nucleosynthesis. The theory of Tsallis entropy, and it’s impact on the Maxwell Boltzmann distribution was studied. Then, the new reaction rates were calculated using the non extensive statistics. The abundances of light nuclei were calculated using a BBN code implemented in python. The python project description is available at: https://pypi.org/project/BBN/#description. By adding a non-extensive parameter (q), the abundances of primordial abundances of light nuclei are in better agreement with the observed values. The predictions can be improved by using a more vast code that includes additional reactions along with their reverse reaction rates, where all the rates are calculated in the Tsallis framework. But even with the limitations of this project, we can observe that the Lithium abundances are better predicted in this non extensive framework and this might be a possible solution to the Lithium problem.