In this study, we have developed and rigorously evaluated four spectral simulation techniques, paired with three padding and three matching strategies, benchmarking them across varied tasks and quality metrics. An overview of our work, contributions, and findings is presented in Figure . The upper-left quadrant outlines the four simulation techniques employed: two commercially available solutions (ACD, MNova), Gaussian NMR calculations (DFT), and a machine learning (ML) method. Additionally, we have implemented an algorithm to reconstruct HSQC spectra from 1D NMR shifts for DFT and ML, taking into account critical factors like symmetry and chirality.