Abstract The voluntary feed intake of the dairy cow is an important variable in dairy operation but is impossible to measure individually when cows are kept in groups or grazing. Existing formulas that calculate dry matter intake (DMI) from ration and performance variables are not applicable to an individual cow for online decision-making, such as daily ration density adjustment by computerized feeders in a milking robot. This led to a new DMI modeling approach of using only animal factors that are measurable online on an individual basis. In 1997 we published a small-scale attempt of this approach using milk yield (MY) and body weight (BW). In 2001, this approach was adopted by the National Research Council (NRC), using 4% fat-corrected milk rather than MY together with BW and time after calving. In the present study, we increased the number of cows. The model is a multiple regression, where the descriptive variables are the interrelation MY/BW, daily BW change, and milk fat including the effect of previous 2 d. The coefficients are calculated on daily basis, i.e., each day has its own coefficients. Our model differs from that of the NRC by: 1) the descriptive variable, 2) using daily coefficients to deal with the ever-changing physiological state of lactation, and 3) considering previous performance. Two data sets (60 cows together) acquired in 2 intervals of the Volcani Center herd were used to calibrate (18 cows) and test (42 cows) the model. Model validity was statistically tested, compared to that of the NRC, and was not rejected with 99.5% confidence.