Dengue is a global health problem. There has been an increase in dengue cases more than 15 times over the last two decades. Therefore, effective tools for surveillance, prevention, and control are needed. This review aimed to provide a systematic overview of the predictors and modeling approaches to generate dengue risk maps. Studies references is a Systematic Review that follows the guidelines for systematic reviews from PRISMA. Researchers searched electronic databases such as PubMed, Scopus, and ScienceDirect. Keywords based on Population, Intervention, Comparison, Outcome (PICO) formulation. Studies were organized by inclusion and exclusion criteria and evaluated using an evidence-based critical assessment checklist adapted for a cross-sectional study using the Newcastle Ottawa scale. Various predictors and models were used to create a dengue risk map, and no specific pattern was identified in the combination of predictors or models. The most widely and commonly used predictors for demographic and socioeconomic categories are land cover, age, education, housing conditions, and income level. Environmental categories are rainfall and temperature, which are significant predictors. Generally, the model is divided into statistical and expert-based approaches. Most available dengue risk maps are based on descriptive and retrospective data. Despite the limitations, the risk map facilitates decision-making in public health. Mobile devices can be optimized to describe dengue transmission dynamics through human movement from dengue serological profile data.