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This study describes the use of Quantitative Structure Activity Relationships (QSAR) to develop predictive models for non-acidic Lubricity agents. The work demonstrates the importance of separating certain chemical families to give better and more robust equations rather than grouping a whole data set together. These models can then be used as important tools in further development work by predicting activities of new compounds before actual synthesis/testing.