Blood-based proteomics can help improve risk prediction and elucidate biological pathways underlying the development of age-related diseases and multi-morbidity. We assessed the associations of ~10,000 plasma proteins, assayed using Olink and SomaScan platforms, with all-cause mortality, 14 incident diseases and multi-morbidity among 2026 Chinese adults. Cox regression yielded hazard ratios for disease risks associated with specific proteins, after adjusting for confounders and multiple testing. Overall, 984 and 761 proteins were significantly associated with all-cause mortality and multi-morbidity respectively, with top proteins mostly involved in regulating immune responses, inflammation, and cell survival. For all-cause mortality, protein-based risk prediction models outperformed conventional risk factors (C-statistics: 0.825 [0.796-0.853] vs 0.806 [0.774-0.838]) and adding proteins to conventional risk factors improved net reclassification index by 32% (17-47%). Our results illustrate that, regardless of specific proteomic assay platform used, plasma proteins could be used to improve risk prediction and inform prevention and treatment of age-related diseases.