We present an approach to overcome the challenges associated with the increasing demand of high-throughput characterization of technical lignins, a key resource in the emerging bioeconomies. Our approach offers a resort from the lack of direct, simple, and low-cost analytical techniques for lignin characterization by employing multivariate calibration models based on infrared (IR) spectroscopy to predict structural properties of lignins (i.e., functionality, molar mass). By leveraging a comprehensive database of over 500 well-characterized technical lignin samples – a factor of 10 larger than previously used sets – our chemometric models achieved high levels of quality and statistical confidence for the determination of different functional group contents (RMSEPs of 4–16%). However, the statistical moments of the molar mass distribution are still best determined by size-exclusion chromatography. Analyses of over 500 technical lignins offered a great opportunity to provide information on the general variability in kraft lignins and lignosulfonates (from different origins). Overall, the effected savings in analysis time (>>7 h), resources, and required sample mass combined with non-destructiveness of the measurement satisfy key demands for efficient high-throughput lignin analyses. Finally, we discuss the advantages, disadvantages, and limitations of our approach, along with critical insights into the associated chemical-analytical and spectroscopic challenges.