Although microcredentials have gained traction in higher education and industry, they have not yet been widely adopted in schools. One reason is that simply digitizing traditional exams offers limited added value in the highly individualized context of school teaching. This chapter introduces the Learning Progression Certification (LPC) framework, which integrates microcredentials with domain-specific learning progressions to capture and certify students’ knowledge in science, technology, engineering, and mathematics (STEM) education. To illustrate the potential of the LPC framework in a school-based context, we retrospectively apply it to data from a pilot implementation of a 16−20-lesson inquiry-based mathematics unit on the concept of derivatives (N = 365 students, 15 classes). In this prototypical use case, students’ acquiring knowledge was modeled as a network of interconnected knowledge elements. After each major cycle of learning activities, a blockchain-based non-fungible token (NFT) microcredential was hypothetically issued to represent the newly acquired knowledge elements. This illustrative example demonstrates how microcredentials, when embedded in structured learning progressions, can provide a fine-grained, verifiable record of conceptual development, thereby supporting personalized feedback and adaptive instruction. Unlike traditional one-time exams, the LPC framework offers a more dynamic and detailed assessment of student learning trajectories, with potential implications for both formative assessment practices and future certification models in education.