Improving feed efficiency stands as crucial for enhancing livestock sustainability, as it contributes to minimizing production costs animal excretion, and gas emissions due to feed production. Achieving superior feed efficiency necessitates the recording of individual feed intake, a challenge overcome in pigs through costly automatic feeders and RFID transponder-equipped animals. Alternatively, indicators of feed efficiency can be searched in accessible samples like blood and feces. In blood sampled at different periods, transcriptomic information has proven valuable, achieving high accuracy in predicting feed efficiency classes (100%) and quantitative measures (R²=0.80) through machine learning. In both cases, combinations of around 30 gene transcripts were retained as reliable predictors. Combinations between blood molecular networks with the blood metabolome information also provided valuable information on the biology behind feed efficiency phenotype. Feces also provide accessible information: near-infrared spectroscopy was used to develop predictors of individual digestive coefficients, indicative of the efficiency in the first stage of energy and nutrient utilization by animals. Fecal sampling further allows approximation of individual gut microbiota composition through partial sequencing (16S) or full metagenome sequencing. Variability in the gut microbiota composition has then emerged as a potential predictor of digestive and feed efficiency. However, determining the genetic architecture of feed efficiency, a composite trait resulting from multiple biological functions, is still challenging. Yet, with the advent of complete genome sequencing, combining imputed sequence variants and phenotyping in two connected pedigreed pig populations has yielded a substantial dataset- (17,033,057 SNP imputed in 3,505 pigs), facilitating the detection of novel genomic regions influencing feed efficiency, related production traits and microbiota traits. Altogether, these high-throughput techniques provide an improved understanding of the factors influencing feed efficiency, paving the way for targeted improvements of livestock sustainability.