The composition of immune cells in peripheral blood is dramatically remodeled throughout the human lifespan, as environmental exposures shape the proportion and phenotype of cellular subsets. These dynamic shifts complicate efforts to identify disease-associated immune signatures in type 1 diabetes (T1D), which is variable in age of onset and rate of beta-cell decline. Herein, we conducted standardized flow cytometric immune profiling on peripheral blood from a cross-sectional cohort of T1D participants (n=240), their first-degree relatives (REL, n=310), those at increased risk with two or more islet autoantibodies (RSK, n=24), and autoantibody negative healthy controls (CTR, n=252). We constructed an immune-age predictive model in healthy subjects and developed an interactive data visualization portal (ImmScape; https://ufdiabetes.shinyapps.io/ImmScape/). When applied to the T1D cohort, this model revealed accelerated immune aging (p<0.001) as well as phenotypic signatures of disease after age correction. Of 192 investigated flow cytometry and complete blood count readouts, 46 were significantly associated with age only, 25 with T1D only, and 23 with both age and T1D. Phenotypes associated with T1D after age-correction were predictive of T1D status (AUROC=82.3%). Phenotypes associated with accelerated aging in T1D included increased CXCR3+ and PD-1+ frequencies in naive and memory T cell subsets, despite reduced PD-1 expression levels (mean fluorescence intensity) on memory T cells. Additionally, quantitative trait locus analysis linked an increase in HLA-DR expression on monocytes with the T1D-associated HLA-DR4/DQ8 genotype, regardless of clinical group. Our findings demonstrate advanced immune aging in T1D and highlight disease-associated phenotypes for biomarker monitoring and therapeutic interventions.