This article discusses the integration of multi-criteria evaluation (MCE) with geographical information systems (GIS) to enhance spatial decision-making. GIS provides powerful tools for spatial data analysis, but its functionality is limited to deterministic analyses. MCE techniques allow users to evaluate alternatives based on multiple, conflicting criteria and objectives. The article presents an example of using MCE with GIS to identify suitable sites for radioactive waste disposal in the UK. It highlights the potential of combining GIS and MCE in developing spatial decision support systems (SDSS). MCE techniques are introduced, including ideal point analysis, hierarchical optimization, and concordance–discordance analysis. The article discusses the limitations of GIS overlay analyses and how MCE can overcome these by providing a more comprehensive evaluation of multiple criteria. It also addresses practical problems in implementing MCE within GIS, such as data input, weighting schemes, and sensitivity analysis. The article concludes that integrating MCE with GIS offers a valuable approach for spatial decision-making, particularly in complex situations involving multiple criteria and conflicting objectives. The integration of MCE with GIS can lead to more rational, objective, and non-biased decision-making processes. However, the effectiveness of these tools depends on the expertise of the user and the availability of appropriate data. The article emphasizes the importance of combining GIS and MCE to develop effective SDSS for spatial decision-making.This article discusses the integration of multi-criteria evaluation (MCE) with geographical information systems (GIS) to enhance spatial decision-making. GIS provides powerful tools for spatial data analysis, but its functionality is limited to deterministic analyses. MCE techniques allow users to evaluate alternatives based on multiple, conflicting criteria and objectives. The article presents an example of using MCE with GIS to identify suitable sites for radioactive waste disposal in the UK. It highlights the potential of combining GIS and MCE in developing spatial decision support systems (SDSS). MCE techniques are introduced, including ideal point analysis, hierarchical optimization, and concordance–discordance analysis. The article discusses the limitations of GIS overlay analyses and how MCE can overcome these by providing a more comprehensive evaluation of multiple criteria. It also addresses practical problems in implementing MCE within GIS, such as data input, weighting schemes, and sensitivity analysis. The article concludes that integrating MCE with GIS offers a valuable approach for spatial decision-making, particularly in complex situations involving multiple criteria and conflicting objectives. The integration of MCE with GIS can lead to more rational, objective, and non-biased decision-making processes. However, the effectiveness of these tools depends on the expertise of the user and the availability of appropriate data. The article emphasizes the importance of combining GIS and MCE to develop effective SDSS for spatial decision-making.