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.