Feed efficiency (FE), the difference between energy intake and the energy demanded and supplied by various reservoirs and sinks, is of increasing importance. One such energy sink is methane emissions (ME); ME also have repercussions on climate change. Collection of the necessary data for the computation of genetic evaluations for both FE and ME are, however, laborious and expensive. Mid-infrared spectrometry (MIRS) offers a solution to routinely collect data on milk recorded animals at no additional cost to milk recording. The use of MIRS to accurately predict animal and milk traits, including energy balance (EB) and milk fatty acids (FA) has recently been shown and validated. When changes in body mass are zero, EB is mathematically identical to residual feed intake (RFI), a measure commonly used to depict FE. The relationship between ME and milk FA has also been reported. Therefore, it was recently hypothesized that both RFI and ME could also be predicted from milk. Two separate studies were conducted using 1,270 records of RFI from Irish Holstein-Friesians, and 77 records of ME from Belgian Holstein cows. Accuracy (i.e., correlation) of predicting RFI and ME using partial least squares regression on the MIR spectral data was 0.62 and 0.87, respectively, in cross validation. Both studies were limited by small numbers, and have yet to be independently validated. The heritability of MIR-predicted RFI was 0.06, and was lower than the heritability of measured RFI using the same data set (0.10), however the genetic correlation between MIR-predicted and measured RFI was 0.78 using the limited data set. Furthermore, when prediction equations were applied to larger data sets of MIR spectral data, the lactation profile for RFI was in line with expectations based on profiles estimated from measured RFI. The shape of the lactation profile of predicted ME was, however, dependent on stage of lactation. The major limitation precluding FE and ME from breeding programs in the past can be resolved through the use of MIRS on milk recorded animals.