Protein-nucleic acid interactions are inevitable in maintaining the homeostasis of cells. It is vital to have a quantitative understanding of these interactions, generally described in terms of the dissociation constant (Kd)or binding affinity (ΔG) of protein-DNA and protein-RNA complexes. With the increase in the experimental data, there was no well-curated database available specific for protein-nucleic acid-binding affinity and had very few prediction tools with several limitations. Hence, we developed a database, ProNAB, which contains more than 20,000 experimental data for the binding affinities of protein-DNA and protein-RNA complexes. Each entry has comprehensive information on the sequence and structural features of a protein, nucleic acid, and its complex, along with experimental conditions, thermodynamic parameters such as dissociation constant, binding free energy, and cross-linked to other databases. ProNAB is freely available at https://web.iitm.ac.in/bioinfo2/pronab/. To predict the binding affinity of protein-DNA complexes, we filtered the experimental binding affinity of 391 non-redundant complexes. Several structure-based features on DNA, protein, and interactions between protein and DNA were generated to develop multiple regression equations for predicting the binding affinity of protein-DNA complexes. Our method showed an average correlation and mean absolute error of 0.78 and 0.98 kcal/mol on a jackknife test. We have developed a web server, PDA-Pred, and it is freely accessible at https://web.iitm.ac.in/bioinfo2/pdapred/. Further, we also extended our study to predict the protein-RNA binding affinity. We have collected the binding affinity values for a set of 217 protein-RNA complexes and derived several structure-based features. Further, we developed multiple regression equations for predicting the binding affinity of protein-RNA complexes belonging to different classes, which showed an average correlation and mean absolute error of 0.77 and 1.02 kcal/mol, respectively, on a jack-knife test. We have developed a web server, PRA-Pred, for predicting the affinity of protein-RNA complexes, and it is freely available at https://web.iitm.ac.in/bioinfo2/prapred/. We suggest that our methods would serve as a potential resource for understanding the recognition of protein-nucleic acid complexes and developing therapeutic strategies.