Background/Objectives: Chronic lymphocytic leukemia (CLL) is characterized by marked clinical heterogeneity, underscoring the need for reliable biomarkers to improve diagnosis and risk stratification. Extracellular vesicles (EVs) represent promising liquid biopsy candidates because they reflect the molecular profile of their cells of origin. In CLL, CD200 is a well-established marker of tumor cells; its expression on EVs and its role as a CLL biomarker were poorly characterized. This study investigated the diagnostic and prognostic value of serum EVs in CLL. Methods: Serum EVs were isolated from 83 patients with CLL and 20 healthy subjects (HS). EV morphology, size, and concentration were assessed by transmission electron microscopy and nanoparticle tracking analysis. Flow cytometry was used to evaluate the expression of CD19, CD20, and CD200 on EVs, while digital PCR quantified EV-associated miR-93-5p, miR-125b-5p, miR-150-5p, and miR-484. Results: Compared with HS, CLL patients showed increased total EV counts and higher levels of CD19⁺, CD20⁺, CD200⁺, and CD19⁺/CD20⁺ EVs, together with enhanced CD20 and CD200 expression and reduced miR-93-5p, miR-125b-5p, and miR-484 levels. In contrast, EV-associated miR-150-5p levels were comparable between CLL patients and HS. EV features were correlated with clinical and biological characteristics, including disease stage, cytogenetic abnormalities, treatment, and time to treatment (TTT). Older age was associated with lower EV concentrations but higher CD20 and CD200 expression. Advanced-stage disease was characterized by smaller EVs with increased CD200 expression. Notably, elevated CD200⁺ EV levels and reduced CD19 expression were associated with shorter TTT and earlier treatment initiation. Conclusions: Multiparametric profiling identified distinct quantitative, phenotypic, and molecular features of CLL-derived EVs and revealed CD200 as a novel EV-associated biomarker. These findings support the clinical utility of serum EVs as a new valuable approach for CLL diagnosis, prognosis, and treatment prediction.