Soil quality index shed light on soil health and its capacity to sustain high primary production. It also can assist decision-making in farming systems by integrating this valuable product into soil management planning. However, the currently existing models are based on rather local data, and thus, there is a lack of predictive tools to monitor soil quality on farming systems at tropical conditions. We characterized soil physico-chemical properties, plant biomass production under a 6-year experiment in a sandy soil from Tropical ecosystem, using ten treatments: Brachiaria decumbens, Canavalia ensiformis, Crotalaria juncea, Crotalaria ochroleuca, Crotalaria spectabilis, Lablab purpureus, Mucuna pruriens, Neonotonia wightii, Pennisetum glaucum, and Stilozobium aterrimum. We found that most of the soil physico-chemical properties were correlated with each other by Pearson’s correlation analysis. On the other hand, RDA illustrated that shoot dry biomass was related to soil C stock, K+, macro- and microporosity. Soil pH, Al3+, Ca2+, Mg2+, K+, Olsen’s P, Na+, soil C stock, bulk density, microporosity, macroporosity, and permanent wilting point were the main factors driving primary production in our long-term study. Our findings suggest that: 1) a consecutive green manure practice without any input of fertilizers after 6 years changed positively by increasing soil fertility (e.g., Ca2+, Mg2+, K+ and Olsen’s P), and improving plant growth and soil quality in tropical savanna climate conditions; and 2) the 33 multivariate predictive models may provide a deeper view about the benefits of using plant species as green manure by creating positive plant-soil feedback thus promoting soil quality.