MS dissociation methods, including CID, HCD, and ETD, can each contribute distinct peptidome identifications using conventional peptide identification methods (Shen et al. J. Proteome Res. 2011), but such samples still pose significant informatics challenges. In this work, we explored utilization of high accuracy fragment ion mass measurements, in this case provided by FT MS/MS, to improve peptidome peptide dataset size and consistency relative to conventional descriptive and probabilistic scoring methods. For example, we identified 20–40% more peptides than SEQUEST, Mascot, and MS-GF scoring methods using high accuracy fragment ion information and the same FDR (e.g., 90% of the collective identifications obtained using various conventional peptide identification methods, which resolves the issue of different data analysis methods generating different peptide datasets. Choice of peptide dissociation and high-precision measurement-based identification methods presently available for degradomic-peptidomic analyses needs to be based on the coverage and confidence (or specificity) afforded by the method, as well as practical issues (e.g., throughput). By using accurate fragment information, >1000 peptidome peptides can be identified from a single human blood plasma sample with low peptide-level FDRs (e.g., 0.6%), providing an improved basis for investigating potential disease-related peptidome components.