International Journal of Academic and Applied Research (IJAAR)   Year: 2019 | Volume: 3 | Issue: 2 | Page No.: 1-8 Prediction of Whether Mushroom is Edible or Poisonous Using Back-propagation Neural Network. Eyad Sameh Alkronz, Khaled A. Moghayer, Mohamad Meimeh, Mohannad Gazzaz, Bassem S. Abu-Nasser, Samy S. Abu-Naser Abstract: Abstract: Predication is an application of Artificial Neural Network (ANN). It is a supervised learning due to predefined input and output attributes. Multi-Layer ANN model is used for training, validating, and testing of the data. In this paper, Multi-Layer ANN model was used to train and test the mushroom dataset to predict whether it is edible or poisonous. The Mushrooms dataset was prepared for training, 8124 instances were used for the training. JustNN software was used to training and validating the data. The most important attributes of the data set were identified, and the accuracy of the predication of whether Mushroom is edible or Poisonous was 99.25%.