All-solid-state lithium metal batteries (ASSLMBs) with high energy density and ensured safety have been regarded as leading candidates for next-generation energy storage systems. However, many issues of solid-state electrolytes (SSEs) still remain to be conquered. Recently, density functional theory (DFT) calculations have been conducted to explore fundamental properties of the SSEs and reveal the relationship between the structure/composition and intrinsic properties of target materials. In addition, high-throughput screening enables the rapid identification of fast Li-ion conductors based on the features quantified by DFT, making the search for novel SSE materials being convenient. The present review aims to provide insight into the contribution of DFT calculation in developing the SSE materials. A brief overview of the development of DFT will be first described. Then, the role of DFT approach in gaining insight into the intrinsic properties of SSEs, such as structural stability, electrochemical stability, and Li-ion transport mechanism, is highlighted. At last, the progress of high -throughput DFT calculation in screening new SSEs materials is summarized considering the combination of DFT and machine learning (ML) will accelerate fundamental exploration. This present review aims to arouse the interest of theoretical approach in developing novel SSEs for high-performance energy storage systems.