Hybrid vehicles have been widely used for more than 25 years, and their traction batteries are exposed to demanding operating conditions, particularly in urban traffic characterized by frequent regenerative braking and acceleration. Such patterns lead to progressive degradation of cell capacity and performance, highlighting the need for reliable diagnostic and repair methodologies. This article presents a comprehensive approach to traction battery diagnostics and repair for hybrid vehicles. A mobile diagnostic service, equipped with specialized instrumentation, enables simultaneous controlled charge–discharge testing of multiple battery cells. The collected measurement data are analyzed using the Metalog probability distribution family, which offers flexibility and precision in modeling the statistical characteristics of battery degradation. The methodology is demonstrated through three representative case studies of Toyota hybrid vehicle batteries. These cases illustrate different degradation pathways: gradual natural capacity fading, accelerated local overheating, and severe long-term deterioration. For each case, the approach allows for classification of cells and battery packs into categories suitable for further use, repair through selective replacement, or recycling. The integration of engineering diagnostics with statistical modeling significantly improves the accuracy of state-of-health assessments and supports efficient decision-making in practice. The mobile service context further demonstrates the method’s applicability, allowing diagnostics and repair to be performed directly at the customer’s site. The findings highlight both the economic benefits, by reducing the cost of battery replacement and extending vehicle lifetime, and the ecological advantages, by enabling second-life applications and supporting safe recycling. Thus, the proposed methodology contributes to sustainable battery management and strengthens the role of diagnostics in advancing electromobility.