Visual animal biometrics is an emerging research discipline in computer vision, pattern recognition and cognitive science. It is a promising research field that encourages new development of quantified algorithms and methodologies for representing, detection of visible features, phenotypic appearances of species, individuals and recognition of morphological and animal biometric characteristics. Furthermore, it also assists the study of animal trajectory and behaviours analysis of species. Currently, real-world applications of visual animal biometric systems are gaining more proliferation due to a variety of applications and use, enhancement of quantity and quality of the collection of extensive ecological data and processing. However, to advance visual animal biometrics will require integration of methodologies among the scientific disciplines involved. Such valuable efforts will be worthwhile due to the enormous perspective of this approach rests with the formal abstraction of phenomics, to build well-developed interfaces between different organisational levels of life. This study provides a comprehensive survey of visual animal biometric systems and recognition approaches for various species and individual animal based on their morphological image pattern and biometric characteristics. This comprehensive review paper encourages the multidisciplinary researchers, scientists, biologists and different research communities to design the better platforms for the development of efficient algorithms and learning models to solve the massive data processing, classification and identification of different species related problems.