To understand the implications of protein glycosylation for clinical diagnostics and biopharmaceuticals, innovative glycoproteomic technologies are required. Recently, significant advances have been made in such technologies, particularly in the area of structure-focused N-glyco-proteomic analyses. Mass spectrometric analysis of intact N-glycopeptides using stepped collision fragmentation along with glycan oxonium ion profiling now makes it possible to reliably discriminate between different N-glycan structures. Still, current N-glycoproteomic approaches have weaknesses that must be overcome, namely ① the handling of incorrect identifications, ② the identification of rare and modified N-glycans, and ③ insufficient glycoproteomic coverage, especially in complex samples. To address these shortcomings, we have established an innovative N-glycoproteomic workflow that aims to provide comprehensive site-specific and structural N-glycoproteomic data on human blood plasma (HBP) glycoproteins. The workflow features protein depletion plus a fractionation strategy and the use of high-resolution mass spectrometry with stepped collision fragmentation. Furthermore, by including a new decision tree procedure developed for data validation, we can significantly improve the description of N-glycan micro-heterogeneity. Our advanced data analysis workflow allows the reliable differentiation of ambiguous N-glycan structures such as antenna versus core fucosylation, as well as modified and rare N-glycans such as sulfated and glucuronidated ones. With this workflow, we were able to achieve the detection of HBP glycoproteins with reported concentrations within the ng·mL⁻¹ level. A total of 1929 N-glycopeptides and 942 N-glycosites derived from 805 human middle- to low-abundant glycoproteins were identified. Overall, the presented workflow holds great potential to improve our understanding of protein glycosylation and to foster the discovery of blood plasma biomarkers.