In the last decades, the offer of animal products is more and more increasing especially in developing countries due to growing food demand and needs. The activities of the livestock sector impact on climate change with several emissions in particular, Methane (44%), Carbon dioxide (27%) and Nitrous oxide (29%). Cattle emits the highest, about 65% of the livestock production emissions; indeed feed processing and production and enteric fermentation from ruminants are the two major sources of emissions, contributing to 45% and 39% of total emissions respectively. On product-basis, milk from cows and beef are in charge to emit the most emissions. Cattle-farming for dairy and beef production is one of the main most important agricultural activities in Italy. The link between cattle emissions and economic performance is the issue that here has been addressed at the light of the societal challenge increasingly based upon bio-based economies. There are few studies regarding the GHG emissions associated with the cattle production and economic performances. Therefore, the objective of this study is to classify the cattle farm emissions respect to the economic performance variables of Italian cattle farming sector and to classify segment of firms in clusters: for these aims a CHAID decision-tree algorithm and a two-stage method of clustering was carried out. Decisional trees and cluster analysis highlight the significative links between farm emission and profitable variables. Results show the GHG emissions increase with the increase of the production amount, only if the firm handling is not efficient: indeed virtuous cattle farms present a regimented and planned resources management allowing low GHG emissions. This analysis can shed some light on the efforts for reducing GHG emissions deriving from cattle farming, and so following bio-economy pathways to actually equitable, sustainable, post fossil carbon societies.