This dissertation presents a comparative analysis of two approaches of the Fuzzy AHP (Fuzzy Analytic Hierarchy Process) combined with Fuzzy TOPSIS (Fuzzy Technique for Order of Preference by Similarity to Ideal Solution) applied in the supplier segmentation matrix proposed by Rezaei and Ortt (2012). The study aims to evaluate the effectiveness of two methods for sustainable supplier segmentation, differing in the derivation of the criteria weight vector in the fuzzy AHP approach. The first method used the geometric mean method, while the second used the extent analysis method. The results showed that both methods produced similar segmentation matrices, but the geometric mean method was more suitable as it performed better in the comparison criteria analyzed. The segmentation was applied in a dairy company, and the results indicated that the geometric mean method provided a more accurate and effective segmentation of suppliers into four segments based on two dimensions: "supplier's sustainable capabilities" and "supplier willingness to cooperate." The study highlights the importance of using fuzzy methods in supplier segmentation to account for uncertainty and imprecision in decision-making processes. The findings contribute to the field of sustainable supply chain management by providing a practical framework for evaluating and segmenting suppliers based on multiple criteria. The research also emphasizes the need for further studies comparing different segmentation methods and analyzing the sensitivity of segmentation results.This dissertation presents a comparative analysis of two approaches of the Fuzzy AHP (Fuzzy Analytic Hierarchy Process) combined with Fuzzy TOPSIS (Fuzzy Technique for Order of Preference by Similarity to Ideal Solution) applied in the supplier segmentation matrix proposed by Rezaei and Ortt (2012). The study aims to evaluate the effectiveness of two methods for sustainable supplier segmentation, differing in the derivation of the criteria weight vector in the fuzzy AHP approach. The first method used the geometric mean method, while the second used the extent analysis method. The results showed that both methods produced similar segmentation matrices, but the geometric mean method was more suitable as it performed better in the comparison criteria analyzed. The segmentation was applied in a dairy company, and the results indicated that the geometric mean method provided a more accurate and effective segmentation of suppliers into four segments based on two dimensions: "supplier's sustainable capabilities" and "supplier willingness to cooperate." The study highlights the importance of using fuzzy methods in supplier segmentation to account for uncertainty and imprecision in decision-making processes. The findings contribute to the field of sustainable supply chain management by providing a practical framework for evaluating and segmenting suppliers based on multiple criteria. The research also emphasizes the need for further studies comparing different segmentation methods and analyzing the sensitivity of segmentation results.