Accurate evaluation of both electrochemical performance and flexibility is crucial for the successful development and application of flexible batteries. Key assessment parameters fall into three categories: geometric, mechanical, and energy density. Importantly, electrochemical performance strongly depends on operating conditions such as temperature, load current, and state-of-charge (SOC). Therefore, establishing appropriate laboratory characterization methodologies is essential. This involves measuring critical battery parameters (capacity, open-circuit voltage, and impedance) under various operating conditions. Furthermore, performance models have been proposed to parameterize the battery’s equivalent electrical circuit (EEC), enabling emulation of its dynamic behavior and validation of the characterization methodology. Notably, flexible battery reliability can be influenced by both mechanical and chemo-electrical effects. Combining appropriate test setups with physically based machine learning could offer a powerful approach for developing regression models to predict battery state-of-health. This chapter provides a concise overview of key flexible battery assessment parameters, electrochemical performance characterization methods, and reliability characterization approaches.