Plasma is an abundant source of proteins and potential biomarkers to aid in the detection, diagnosis, and prognosis of human diseases. However, these proteins are often present at low levels in the blood and difficult to consistently identify and measure. Quantifying more than a few hundred proteins in neat plasma is difficult due to the large dynamic range, and as much as ~99% of its mass is derived from only ~20 proteins. Abundant protein precipitation with perchloric acid (PerCA) is a high-throughput approach to increase protein identifications and depth of plasma proteomic studies. The goal of this work was to characterize and compare various protein precipitation methods related to plasma proteomic depth and breadth. Three acid-based and four solvent-based precipitation methods were evaluated by mass spectrometry. All methods tested provided excellent plasma proteomic coverage (>600 identified protein groups) and detected protein in the low pg/ml range. Functional enrichment analysis revealed subtle differences within and larger changes between the precipitant groups; acid-based methods enriched for plasma membrane proteins, while solvent-based approaches enriched for lipoprotein particle proteins. Methanol-based precipitation outperformed the other methods based on identifications and reproducibility. The performance of these methods was verified using eight lung cancer patient samples, where >700 protein groups were measured and proteins with an estimated plasma concentration of around 10 pg/ml were detected. In conclusion, a variety of protein precipitation agents are amenable to extending the depth and breadth of plasma proteomes, however, the composition of proteins between agents does vary. These data can guide investigators to implement inexpensive, high-throughput methods for their plasma proteomic workflows.