This book targets research scholars and students interested in neural networks and its applications. It illustrates the efficiency of various algorithms over different types of data sets using bar graphs. Various Neural Network Algorithms are studied and made run on same data set to find out efficiency of each algorithm and the output of all these algorithms are compared. Neural Network Algorithms used are: Decision Tree Forest, Cascade Correlation, Multiple Layer Perceptron, Probabilistic and General Regression Neural Networks, Radial Basis Function Neural Networks, Group Method of Data Handling, polynomial neural networks and Support Vector Machines. Three diseases have been identified for using their data sets: Liver Disorder, Nephritis of renal pelvis origin, Inflammation of urinary bladder. There are certain tests which are needed to be performed to identify a given disease, then that disease is said to be present. We gave the value of those parameters to each algorithm to find which algorithm can predict the correct disease and with what accuracy. Finally, the outputs from all the algorithms are compared. DTREG software is used to run each algorithm and to generate output.