A series of aspartame analogues and chemically modified derivatives was evaluated for their structure-activity relationship, as artificial sweeteners using Three Dimensional Quantitative Structure-Activity Relationship (3D-QSAR) with Genetic Functional Algorithm (GFA). A four-term equation was developed with conventional and cross-validated coefficients of 0.753 and 0.660, respectively. 3D-QSAR studies of the same series were also performed by Comparative Molecular Field Analysis (CoMFA) and Comparative Molecular Similarity Indices Analysis (CoMSIA). The CoMFA model produced modest statistical significance with conventional and cross-validated correlation coefficients of 0.768 and 0.390, respectively. The combination of steric, electrostatic, hydrophobic, and H-bond acceptor fields in CoMSIA gave better results with conventional and cross-validated correlation coefficients of 0.927 and 0.585, respectively. The predictive ability of 3D-QSAR with GFA, CoMFA, and CoMSIA were determined using a test set of ten molecules giving predictive correlation coefficients of 0.375, 0.535, and 0.596, respectively, indicating better predictivity of CoMSIA compared to the other methods. Based on this information, some key features that may be used to design new sweeteners and predict their sweetness value have been identified.