Soil represents one of the most important reservoirs of biodiversity. It reflects all the bio-geo-chemical processes of the different ecosystem components; therefore soil quality fluctuations are considered to be a suitable criterion for evaluating the long-term sustainability of ecosystems. In ecosystem and soil science survey, understanding the relationship among soil, landscape, vegetation and soil fauna as important components in soil formation is necessary for better and more sustainable management of forest lands. For this purpose, this study was conducted in three related studies including; i) investigating the relationship among soil characteristics, landscape, vegetation and soil fauna, ii) prediction of the abundance and biodiversity of soil fauna, and iii) prediction of soil microorganisms in Shast-Kalate forest with an approximate area of 900 hectares in Golestan province, northern Iran. In order to achieve the objectives of this study, the geological map and parcels map of the forest were investigated and the location of 153 plots was determined. In each plot, sampling was performed using a metal frame with dimensions of 10 × 10 × 20 cm. The results of this study showed that the studied area has a clay loamy texture and soils are acidic to neutral. Relationships among soil fauna, soil characteristics and environmental parameters showed that the abundance and indexes of biodiversity of soil invertebrates are significantly affected by depth. Soil invertebrates in the first depth were twice larger than second depth. The results showed that soil properties, electrical conductivity, organic carbon, total nitrogen, sand and microbial respiration were affected by depth. Also, the abundance and biodiversity indexes of soil invertebrates were significantly affected by soil depth. Soil characteristics including pH, electrical conductivity, organic carbon, total nitrogen and microbial respiration showed a significant correlation with soil biodiversity indexes, while topographic parameters and vegetation indices didn’t show a strong linear relationship with invertebrates, and their impact is likely to be indirect and through the effect on soil properties. Since the abundance and biodiversity of soil invertebrates is related to the environmental conditions induced by the interaction between soil characteristics, soil moisture and surface temperature (influenced by topographic and vegetation parameters). Therefore, these interactions produce complex changes in environmental parameters, which lead to different patterns of soil invertebrates’ distribution. Results showed that Random Forrest model has a higher accuracy and less error than other models in predicting abundance, diversity index and richness of invertebrates in the first and second depths. Also, according to the prediction map of abundance and collected invertebrates from plots, it can be concluded that there is an acceptable agreement between the observed and predicted values and the obtained maps can provide well information on the distribution of soil fauna. Also, studying and modeling of soil microorganisms showed that Protozoa and gram-positive bacteria were the least and the most of the microorganisms of the studied samples, respectively, and there is a significant relationship between organic carbon and nitrogen with all soil microbial groups. Also, in modeling and predicting soil microorganisms, artificial neural network model has higher accuracy and less error than linear regression and Random Forrest models and can justify more changes. Also, distribution of microorganisms was associated with topographic characteristics and vegetation indices, and the use of these indices allows for the modeling of soil replicas with higher precision. Key Words Topography, Vegetation, Soil invertebrates, Soil microorganisms, Modelling, Mapping.