Detailed species geographical distribution is fundamental to ecology management and conservation strategies. Compared with the considerable effort needed for direct population estimates, obtaining presence/absence data are more practical and economically effective, so the methods on mapping species distribution with presence/absence data and related environmental variables have been well developed in recent decades with broad implications. The key steps for species distribution modeling using presence/absence data include: 1) develop the conceptual model, 2) collect presence/absence data and prepare environmental variable layers, 3) select statistic model and algorithm, and 4) run the model and conduct model evaluation. Conceptual models propose the hypothesis of the research and build outlines for data preparation and statistical methods. Systematic sample and non-systematic sampling are used to collect presence/absence data. Related environmental variables are selected and georeferenced by GIS tools to be used in species distribution models at a proper scale. We summarized the algorithms and software that have been used to develop species distribution models combining presence/absence data and environmental variables. Assessment of model performance is crucial for implicating the results generated by those models. This paper reinvented the details of techniques for the above steps of species distribution models. We expect that this paper will show readers some revelation on how to use species distribution models.