The optimization of block?level urban space from a walking?oriented perspective is of profound and enduring significance for enhancing urban travel efficiency, promoting low?carbon and sustainable mobility, and improving the overall quality, livability, and resilience of the human settlement environment. As cities worldwide increasingly embrace the vision of walkable, human?scale neighborhoods and compact urban forms, a systematic, comprehensive, and operational understanding of how block spaces can be optimized to facilitate and incentivize pedestrian activity has become both a theoretical imperative and an urgent practical necessity for planners and decision?makers. However, existing review studies in this domain have predominantly concentrated on delineating the evolution of theoretical frameworks and developmental trajectories of walking and pedestrian research, whereas comparatively insufficient attention has been devoted to the concrete spatial optimization methods, advanced analytical techniques, and implementable planning models that can directly inform, guide, and evaluate real?world planning and design practice. To address this issue, this study employs a combination of systematic literature research and logical analysis to review, refine, and reflect upon the optimization system of block spaces under the guidance of walking travel, following an integrated analytical logic of “theoretical foundation-problem orientationmethodological support-pattern extraction-optimization practice”. First, the paper integrates multi?dimensional theoretical foundations, including Environmental Behavior Theory, the Hierarchy of Walking Needs, and the 5D Built Environment Theory (density, diversity, design, destination accessibility, and distance to transit), in order to systematically deconstruct and articulate the cumulative effect, feedback mechanisms, and spiral?upward logic of walking?oriented block space optimization. This conceptual logic emphasizes that optimization is not a one?time, static intervention but a continuous, iterative process of feedback, learning, adjustment, and refinement. On this basis, the study establishes a comprehensive and logically coherent methodological system categorized into three hierarchical levels. “Epistemology” focuses on scientific cognition and knowledge acquisition through multi?source big data (such as GPS trajectories, mobile signaling data, and street?view images) to achieve precise, fine?grained measurement of pedestrian behavior patterns and environmental characteristics. “Interpretation” delves into deep attribution analysis using statistical models, machine?learning algorithms, and rigorous causal identification methods to reveal and quantify the mechanisms linking the built environment to walking propensity and behavioral responses. “Prediction” utilizes multi?scenario simulation tools such as Agent?Based Modeling (ABM), Virtual Reality (VR), and related digital simulation platforms to pre?evaluate, compare, and optimize the potential impacts of alternative planning interventions. Furthermore, the research systematically summarizes and refines four dominant optimization patterns: Land?Use Regulation, which focuses on structural optimization and functional mixing to enhance land?useefficiency and spatial compactness; Network Connectivity, which aims to optimize the topology and continuity of walking paths to break spatial silos, reduce fragmentation, and improve overall accessibility; Functional Enrichment, which ensures that the supply of daily services and public facilities aligns with the concept of the “15?minute community life circle” to meet diverse resident needs in terms of living, working, and leisure; and Environmental Enhancement, which targets the improvement of micro?scale visual elements, greenery, and street furniture to foster social interaction, walking comfort, perceived safety, and psychological well?being. These four models are illustrated and validated through international benchmarks such as Barcelona’s Superblocks and New York’s Complete Streets, as well as localized Chinese innovations exemplified by Shanghai’s community life circles and other emerging neighborhood?scale experiments. The review identifies and highlights that the prevailing paradigm of walking?oriented optimization is undergoing a profound shift from singular, project?based physical renovations toward integrated, systemic social?spatial governance and coordinated policy design. Finally, the paper proposes that future research should focus on three key directions: Multidisciplinary Synergy, to more fully integrate insights from psychology, public health, transportation engineering, and data science into a shared research agenda; Integrated Technical Methods, to move from simple correlation analysis toward robust causal inference and dynamic feedback evaluation using digital twin technologies and high?resolution urban models; and Multi?scale Spatial Linkage, to resolve the scale?dependent biases and mismatches in planning and to ensure that micro?node improvements at the street and block level meaningfully contribute to macro?network resilience and citywide equity. By fostering an organic unity between theoretical deepening and practical application, this study provides a solid scientific foundation and a strategic roadmap for creating more walkable, sustainable, inclusive, and human?centric urban block environments in the future.