Relevance. Humanity is currently facing a number of environmental challenges, the most significant of which is climate change. The main factor driving climate change is global warming caused by substantial greenhouse gas emissions. One of the key approaches to addressing this issue is the integration of renewable energy sources. However, the intermittent nature of their operation necessitates the use of energy storage systems to ensure uninterrupted power supply for consumers. In this context, lithium-ion batteries are among the most promising energy storage devices due to their high specific energy, long cycle life, and efficiency. During operation, lithium-ion batteries are exposed to the risk of thermal runaway – a difficult-to-predict phenomenon that may lead to severe accidents. Therefore, the task of timely prediction of pre-failure states in lithium-ion batteries becomes highly relevant from the perspective of safety assurance. Direct experimental studies of failure states are associated with high costs and technical difficulties, since batteries typically become unsuitable for further use after thermal runaway. This highlights the practical significance of developing a voltage model of the battery at the pre-failure stage. Aim. To develop a voltage model of a lithium-ion battery in a pre-failure state arising, for example, under overcharge conditions. Methods. Experimental published battery voltage data in the pre-failure regime, along with mathematical and numerical methods for approximating the characteristics and constructing the corresponding dynamic voltage model of the lithium-ion batteries. Results and conclusions. The study demonstrates that the developed model adequately characterizes the voltage dynamics of the battery under overcharge conditions. Compared with the reference model, the maximum error of the refined model is approximately 6.5%, while the mean relative error is 0.6%, confirming the effectiveness of the proposed approach for predictive applications.