Low-cost feeding-behavior sensors will soon be available for commercial use in dairy farms. The aim of this study was to develop a feed intake model for the individual dairy cow that includes feeding behavior. In a research farm, the individual cows' voluntary feed intake and feeding behavior were monitored at every meal. A feed intake model was developed based on data that exist in commercial modern farms: 'BW,' 'milk yield' and 'days in milking' parameters were applied in this study. At the individual cow level, eating velocity seemed to be correlated with feed intake ( R 2 = 0.93 to 0.94). The eating velocity coefficient varied among individuals, ranging from 150 to 230 g/min per cow. The contribution of feeding behavior (0.28) to the dry matter intake (DMI) model was higher than the contribution of BW (0.20), similar to the contribution of fat-corrected milk (FCM)/BW (0.29) and not as large as the contribution of FCM (0.49). Incorporating feeding behavior into the DMI model improved its accuracy by 1.3 (38%) kg/cow per day. The model is ready to be implemented in commercial farms as soon as companies introduce low-cost feeding-behavior sensors on commercial level.Keywords: individual cow, eating speed sensor, precision livestock farming ImplicationsFeed is the greatest expense in milk production. However, monitoring the individual cow's feed intake is currently only economically feasible under research conditions. Existing nutrition models to predict feed intake may only fit groupwise. It can be assumed that low-cost feeding-behavior sensors will soon be available for commercial use in many farms. The aim of this study was to develop a feed intake model for the individual dairy cow that includes feeding behavior. IntroductionFeed is the greatest expense in milk production (Buza et al., 2014). Knowledge of the individual dairy cow's voluntary dry matter intake (DMI) could contribute to the design of more efficient animal nutrition, at either the group level, summing more accurate predictions of all individual cows concurrently presented in a group (Maltz et al., 2013) or the individual cow level. At the latter level, the design of an individualized animal diet is required when computerized concentrate self-feeders either standalone (Livshin et al., 1995) or are built into a milking robot stall (Halachmi, 2004 and2005;Madsen et al., 2010).However, monitoring the individual cow's feed intake is currently only feasible under research conditions (Halachmi et al., 1996 and1998;Calan, 1997;Schwartzkopf-Genswein et al., 1999;Grant and Albright, 2001;Huisma, 2002;DeVries et al., 2003;Bach et al., 2004;Ferris et al., 2006;Wang et al., 2006;Chapinal et al., 2007;Mendes et al., 2011;Krawczel et al., 2012). Therefore, several nutrition models have been developed to predict feed intake, but even the best models have been unable to account for >70% of the variation in intake (Vandehaar, 1998;Shelley, 2013), that is, the existing models may only fit groupwise (Arnerdal, 2005). A DMI model at the individual cow level require...