The rapid electrification of the automotive industry has created an urgent demand for lightweight, high-strength battery enclosure systems, positioning composite materials—including sheet molding compound (SMC), bulk molding compound (BMC), carbon fiber reinforced polymer (CFRP), and glass fiber reinforced polymer (GFRP)—as the dominant solution over traditional metallic alternatives. As the foundational tooling governing dimensional accuracy, surface quality, fiber orientation, and production efficiency, composite mold design is critical to translating the theoretical advantages of lightweight materials into manufacturing reality. This review provides a systematic synthesis of current knowledge on composite mold design for battery enclosures and upper covers, organized into five thematic sections covering mold structural design encompassing cavity architecture, mold material selection, and surface engineering; molding process control spanning compression molding, high-pressure resin transfer molding (HP-RTM), long fiber thermoplastic direct processing (LFT-D), and prepreg compression molding (PCM); simulation-driven design integrating finite element analysis (FEA), topology optimization, and ply-level analysis; intelligent mold technologies featuring real-time sensor monitoring, machine-learning-based process control, and predictive maintenance; and green manufacturing and multi-material integration addressing sustainability, recyclability, and regulatory compliance. The main contribution of this work lies in establishing a holistic framework that bridges material science, process engineering, and computational modeling for battery enclosure mold design, with particular emphasis on the convergence of additive manufacturing, artificial intelligence-driven optimization, and stringent safety regulations that will define the next decade of battery enclosure innovation. Compared to existing literature, this review uniquely integrates process-parameter mapping with mold-design requirements and provides actionable guidelines for selecting molding technologies based on production volume, weight reduction targets, and cost constraints.