Hydroelectric power plants provide flexibility services for grid reliability and stability. These flexibility services are particularly useful for integrating variable renewable energy (VRE) resources such as wind and solar. The U. S. Department of Energy (DOE) is sponsoring the Hydropower Flexibility Framework (HFF) project to develop a Flexibility Services Directory (FSD), a Plant Capabilities and Constraints Catalog (PCCC), and a Flexibility Framework Model (FFM). A hydropower plant’s abilities to provide flexibility services (included in the FSD) depend on its fuel (water availability and water-specific constraints), the plant-specific electrical and mechanical capabilities and constraints, and the environmental and regulatory constraints (included in the PCCC). This paper focuses on the development and demonstration of the Flexibility Framework Model. The FFM is an innovative, water-based methodology for analyzing and evaluating alternative energy and ancillary services operations. FFM provides an organizing framework (1) to evaluate the effects of these capabilities and constraints on the various types of flexibility operations and services that could potentially be supplied; and (2) to enable more appropriate decision making for investments in plant equipment, for plant operations, for improved understanding of costs and effects from environmental regulations, and for understanding risks associated with climate related changes in hydrology. The FFM includes a calculation engine that co-optimizes energy, regulation, and spinning reserves. Its components are an associated reservoir curve, the minimum/environmental flow characteristics, and a plant model. The reservoir curve includes the reservoir volume versus elevation, and the plant schedule includes the minimum flow characteristics. The plant model, which enables the optimized plant efficiency calculations, includes optimized plant efficiency matrices, optimized regulation matrices, spinning reserve energy losses based on the spin deployment probability, and peak efficiency matrices. The paper provides the results from multiple analyses using the FFM methodology.