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Simple Summary: The self-organizing map (SOM), an unsupervised artificial neural network model, has emerged as a tool for analyzing insect species assemblages associated with geographic regions. By comparing regions that share similar pest assemblages, SOM provides available information to rank potential invasive species. Scale insects, an important group of Hemiptera, attract a great deal of attention from researchers and quarantine authorities due to their significant threats to crops and ornamental plants. There are few studies on distribution pattern and predicting the invasion of scale insects at a global scale. In the present study, a global presence⁄absence dataset, including 2486 scale insect species in 157 countries, was extracted to assess the establishment risk of potential invasive species based on a self-organizing map (SOM). We provide preliminary establishment risk assessments of numerous scale insects at a global scale and confirm that SOM can be a reliable tool for analyzing a large number of species simultaneously. In the present study, a global presence/absence dataset including 2486 scale insect species in 157 countries was extracted to assess the establishment risk of potential invasive species based on a self-organizing map (SOM). According to the similarities in species assemblages, a risk list of scale insects for each country was generated. Meanwhile, all countries in the dataset were divided into five clusters, each of which has high similarities of species assemblages. For those countries in the same neuron of the SOM output, they may pose the greatest threats to each other as the sources of potential invasive scale insect species, and therefore, require more attention from quarantine departments. In addition, normalized ζi values were used to measure the uncertainty of the SOM output. In total, 9 out of 63 neurons obtained high uncertainty with very low species counts, indicating that more investigation of scale insects should be undertaken in some parts of Africa, Asia and Northern Europe. [ABSTRACT FROM AUTHOR]