Early embryonic development is a highly precise and tightly regulated biological process that directly influences subsequent embryo implantation, pregnancy outcomes, and postnatal health. Establishing a high-resolution spatiotemporal reference model for early embryonic development, particularly in humans, is essential for deciphering early cell fate decisions and assessing key developmental events. We have developed a comprehensive, accurate, and scalable reference model for single-cell gene expression in human early embryos, along with a lineage prediction tool, thereby establishing a universal benchmark for transcriptomic evaluation in early embryonic models (PMID: 39543283, https://petropoulos-lanner-labs.clintec.ki.se/). In this study, we aim to extend the existing reference tool to later developmental stages by integrating spatial transcriptomic data from late gastrulation and single-cell transcriptomic data from the first-trimester placenta with predictive capacity. By leveraging advanced matching algorithms, we seek to enable the precise mapping of transcriptomic data onto spatial contexts. This will allow us to construct a high-resolution spatiotemporal reference, encompassing key developmental lineages and critical time points in embryonic development.