Ecosystem-based fisheries-management (EBFM) is increasingly used in the United States (U.S.), including in the Gulf of Mexico (GOM). Producing distribution maps for marine organisms is a critical step in the implementation of EBFM. In particular, distribution maps are important inputs for many spatially-explicit ecosystem models, such as OSMOSE models, as well as for biophysical models used to predict annual recruitment anomalies due to oceanographic factors. In this study, we applied a recently proposed statistical modelling framework to produce distribution maps for: (i) younger juveniles (ages 0-1) of red snapper (Lutjanus campechanus), red grouper (Epinephelus morio), and gag (Mycteroperca microlepis), so as to be able to define the potential larval settlement areas of the three species in a biophysical model; and (ii) the functional groups and life stages represented in the OSMOSE model of the West Florida Shelf ("OSMOSE-WFS"). This statistical modelling framework consists of: (i) compiling a large database blending all of the encounter/non-encounter data of the GOM collected by the fisheries-independent and fisheries-dependent surveys using random sampling schemes, referred to as the "comprehensive survey database;" (ii) employing the comprehensive survey database to fit spatio-temporal binomial generalized linear mixed models (GLMMs) that integrate the confounding effects of survey and year; and (iii) using the predictions of the fitted spatio-temporal binomial GLMMs to generate distribution maps. This large endeavour allowed us to produce distribution maps for younger juveniles of red snapper, red grouper and gag and nearly all of the other functional groups and life stages represented in OSMOSE-WFS, at different seasons. Using Pearson residuals, the probabilities of encounter predicted by all spatio-temporal binomial GLMMs were demonstrated to be reasonable. Moreover, the results obtained for younger juvenile fish concur with the literature, provide additional insights into the spatial distribution patterns of these life stages, and highlight important future research avenues.