This paper investigated the use of mathematical models in predicting the brake specific fuel consumption, and exhaust emissions of a diesel engine in terms of parameters such as load and volume fractions of Fe3O4 magnetic nanoparticles. Regression analysis was performed using the experimental data. The experiments were carried out by dispersing the Fe3O4 nanoparticles in the diesel fuel with the nanoparticle concentrations of 0.4 and 0.8 vol.%. Moreover, the experiments were performed under variable load conditions, for which a direct-injection diesel engine was employed. The predicted values obtained by the regression equations were compared with the values obtained from the experimental measurements. Analysis of variance (ANOVA) of the results at 95% confidence level showed significance in the developed mathematical models. Furthermore, the regression fitted models were able to predict the brake specific fuel consumption and emission characteristics with a correlation coefficient (R-2) in the range of 94%-98% within the domain of experimental variables. In addition, the nanofluid fuel with the nanoparticle concentration of 0.4 vol.% had an optimal value. The results also revealed a dramatic decrease in NOx and SO2 emissions, while a significant increase was observed in the CO emission and smoke opacity by adding magnetic nanoparticles in diesel fuel. (C) 2016 Elsevier B.V. All rights reserved.