International Journal of Academic and Applied Research (IJAAR)   Year: 2021 | Volume: 5 | Issue: 3 | Page No.: 50-58 ANN for Classification of Animal Species Mohammed Khaled Al-Gharabawi, Rand Suhail Abu Al-Araj, Shaima Khalil Abed, Ahmed Nabil Al-Ghoul Abstract: Over 1.5 million living animal species have been described-of which around 1 million are insects-but it has been estimated there are over 7 million animal species in total. Animals range in length from 8.5 micrometres to 33.6 metres. In this paper an Artificial Neural Network (ANN) model, was developed and tested to predict animal species. There are a number of features that influence the classification of animal species. Such as the existence of hair/ feather, if the animal gives birth or spawns, it is airborne, aquatic, predator, toothed, backboned, venomous, has -fins, has-tail, cat-sized, and domestic. A model based on the Multilayer Perceptron Topology was proposed and trained, using data set what was collected from UCI Machine Learning Repository. Evaluation of the proposed model shows that the ANN model is able to correctly predict the animal category with 100% accuracy.