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In agroecosystems, potential species distribution models are extensively applied in pest management strategies, revealing species ecological requirements and demonstrating relationships between species distribution and predictive variables. The Maximum Entropy model was used to predict the potential distribution of five heteropteran key pests in Iran, namely Adelphocoris lineolatus (Goeze) (Hemiptera: Miridae), Lygus pratensis (L.), Apodiphus amygdali (Germar) (Hemiptera: Pentatomidae), Nezara viridula (L.), and Nysius cymoides (Spinola) (Hemiptera: Lygaeidae). A total of 663 samples were collected from different parts of Iran. The altitude and climate variable data were included in the analysis. Based on test and training data, the area under the receiver operating characteristic curve values were above 0.80, the binomial omission test with the lowest presence threshold for all species was statistically significant (< 0.01), and the test omission rates were less than 3%. The suitability of areas in Iran for A. amygdale (Germar) (Hemiptera: Pentatomidae), N. cymoides (Spinola) (Hemiptera: Lygaeidae), A. lineolatus (Goeze) (Hemiptera: Miridae), L. pratensis (L.), and N. viridula (L.) (Hemiptera: Pentatomidae), ranked as 78.86%, 68.78%, 43.29%, 20%, and 15.16%, respectively. In general, central parts of Iran including salt lakes, deserts, and sand dune areas with very high temperatures and windy weather were predicted to be less suitable, while other regions, mainly northern parts, were most suitable. These new data could be applied practically for the design of integrated pest management and crop development programs.