Tawheed, Bhuiyan MustafaMasud, Syed TahmidIslam, Md. ShajedulArif, HossainIslam, Samiul2026-08-272026-08-272019-10-01B. M. Tawheed, S. T. Masud, M. S. Islam, H. Arif and S. Islam, "Application of Machine Learning Techniques in the Context of Livestock," TENCON 2019 - 2019 IEEE Region 10 Conference (TENCON), Kochi, India, 2019, pp. 2029-2033, doi: 10.1109/TENCON.2019.8929721.9781728118956215934422-s2.0-85077723486https://hdl.handle.net/10361/29547The rising, lucrative and profitable Livestock industry is attracting a good number of enthusiastic investors to invest their capital to make a contribution to the country's overall GDP and recover the deficit in meat production. This research provides cattle breed based analysis depending on different related factors, which includes age, the current weight of cattle, the environment it is being reared on, the diet plan it is being given and the geographical region it originated from. The models implemented in this research are the Multiple Linear Regression model, Support Vector Machine model and Decision Tree learning for obtaining precise prediction analysis. Through the outcomes of these regression models, people can get an overall idea about the ideal conditions and specification which they require for making a calculated guess for accurately predicting the expected weight for a specific breed of cattle.2029-2033en-USDecision treesLivestock analysisMachine learningRegression modelsLivestock.Machine learning.Conference Proceeding10.1109/TENCON.2019.8929721