Current iron ore processing generates about 25% of very fine material called iron ore slimes. These slimes are being disposed into tailing ponds owing to their high alumina content (10-15%) despite having good iron values (45-60% Fe). Due to the rapid depletion of high grade iron ores, there is an urgent need to develop effective beneficiation processes for utilization of slimes. The very fine size of the slime particles (< 150 mu m) makes selective dispersion-flocculation a promising route for their beneficiation. In this paper, we present our first principles density functional theory (DFT) results along with full factorial design of dispersion - flocculation experiments results on the beneficiation of iron ore slimes using guar gum as flocculant. DFT computations have been used to compute the interaction energies and explain adsorption mechanisms of guar gum with hematite, goethite, gibbsite and kaolinite surfaces - the main minerals present in the iron ore slimes. The computed results show that guar gum will be selective towards the hematite surface due to strong Fe-O-guar (gum) chemical interactions as compared to only weak hydrogen bonds in the case of the other mineral surfaces. The experiments were designed to study the effect of the three key process parameters namely, pulp density, guar gum dosage and settling time on the beneficiation of iron ore slimes. The experimental data is used to develop models for prediction of yield, iron grade, % alumina and iron recovery in the concentrate. The models thus obtained are utilized to arrive at the optimized process parameters to achieve maximum iron recovery with acceptable iron grades with minimum alumina in the concentrates. These optimized process conditions shall form base line for further scale-up of the process at pilot/plant scale.