Nearest Neighbor Gaussian Processes (NNGP) based models is a family of highly scalable Gaussian processes based models. In brief, NNGP extends the Vecchia's approximation to a process using conditional independence given information from neighboring locations. In this case study, I will briefly review response and latent NNGP models, illustrate how to code NNGP in Stan, and provide examples of implementing NNGP based models in Stan.