Method for assessing a welfare condition of livestock animals, wherein said method comprises performing the following steps in any technically possible order: a) providing one or more livestock animals; b) providing a main location for the livestock animal/s; c) providing at least one audio sensor device, configured to receive one or more vocalization audio signals generated by the livestock animal/s at the main location; d) providing a data processing unit, configured to process the signals received by the audio sensor device, wherein said data processing unit further comprises: - a database of vocalization audio sounds of the livestock animal/s provided in step a), indicative of a reference welfare condition; and, - hardware and/or software means adapted for determining a welfare condition of the livestock animal/s; e) measuring, with the audio sensor device, one or more vocalization audio signals generated by the livestock animal/s at the main location; f) determining, with the data processing unit, a plurality of acoustic features of the data measured in step e), wherein said acoustic features comprise: - at least one of the Mel-Frequency Cepstral Coefficients MFCC3, MFCC4 and MFCC6; - the pitch feature; and - the number of livestock animal vocalizations per unit of time; g) determining, with the data processing unit, one or more livestock animal productive indicators from the acoustic features obtained in step f); h) comparing, with the data processing unit, the livestock animal productive indicator/s obtained in step g) with the database of the data processing unit and establishing a degree of similarity; i) determining, with the data processing unit, a welfare state of the livestock animal/s according to the degree of similarity established in step h). and characterized in that step g) further comprises a prediction of one or more of the following livestock animal productive indicators for a period between 0 to 10 days: body weight, feed intake, water consumption, body temperature, and/or carbon dioxide consumption. a) providing one or more livestock animals; b) providing a main location for the livestock animal/s; c) providing at least one audio sensor device, configured to receive one or more vocalization audio signals generated by the livestock animal/s at the main location; d) providing a data processing unit, configured to process the signals received by the audio sensor device, wherein said data processing unit further comprises: - a database of vocalization audio sounds of the livestock animal/s provided in step a), indicative of a reference welfare condition; and, - hardware and/or software means adapted for determining a welfare condition of the livestock animal/s; - a database of vocalization audio sounds of the livestock animal/s provided in step a), indicative of a reference welfare condition; and, - hardware and/or software means adapted for determining a welfare condition of the livestock animal/s; e) measuring, with the audio sensor device, one or more vocalization audio signals generated by the livestock animal/s at the main location; f) determining, with the data processing unit, a plurality of acoustic features of the data measured in step e), wherein said acoustic features comprise: - at least one of the Mel-Frequency Cepstral Coefficients MFCC3, MFCC4 and MFCC6; - the pitch feature; and - the number of livestock animal vocalizations per unit of time; - at least one of the Mel-Frequency Cepstral Coefficients MFCC3, MFCC4 and MFCC6; - the pitch feature; and - the number of livestock animal vocalizations per unit of time; g) determining, with the data processing unit, one or more livestock animal productive indicators from the acoustic features obtained in step f); h) comparing, with the data processing unit, the livestock animal productive indicator/s obtained in step g) with the database of the data processing unit and establishing a degree of similarity; i) determining, with the data processing unit, a welfare state of the livestock animal/s according to the degree of similarity established in step h).