Computer-aided molecular design (CAMD) is a methodology that has been researched recently for designing materials with required target properties and can be well applied for the selection of safer chemicals in chemical process design. An important aspect of this methodology concerns quantitative structure property relation (QSPR) based studies. The main objective of this work is to provide simple straightforward techniques for the accurate prediction of the lower flammability limits through a robust QSPR approach. The obtained three-parameter multivariate regression (MLR) and adaptive neuro-fuzzy inference system (ANFIS) modeling strategies resulted in encouraging statistics of R-2 = 0.906, RMSE = 0.335 and R-2 = 0.930, RMSE = 0.287 vol.%, respectively, using the entire DIPPR dataset. Using such a large dataset comprising of 1615 compounds from 82 diverse chemical material classes can highly benefit the study accuracy and comprehensiveness. Notably, the model input variables can be easily calculated for non-specialist user. (C) 2011 Elsevier Ltd. All rights reserved.