Additivity in binding affinity of protein-protein complexes refers to the change in free energy of binding (ΔΔG ) for double (or multiple) mutations which is approximately equal to the sum of their corresponding single mutation ΔΔG values. In this study, we have explored the additivity effect of double mutants, which shows a linear relationship between the binding affinity of double and sum of single mutants with a correlation of 0.90. However, the comparison of ΔΔG values showed a mean absolute deviation of 0.86 kcal/mol, and 25.6% of the double mutants show a deviation of more than 1 kcal/mol, which are identified as non-additive. The additivity effects have been analyzed based on the influence of structural features such as accessible surface area, long range order, binding propensity change, surrounding hydrophobicity, flexibility, atomic contacts between the mutations and distance between the 2 mutations. We found that non-additive mutations tend to be closer to each other and have more contacts. We have also used machine learning methods to discriminate additive and non-additive mutations using structure-based features, which showed the accuracies in the range of 0.77-0.92 for protein-protein complexes belonging to different functions. Further, we have compared the additivity effects of protein stability along with binding affinity and explored the similarities and differences between them. The results obtained in this study provide insights into the effects of various structural features on binding affinity of double mutants, and will aid the development of accurate methods to predict the binding affinity of double mutants.