<b>A Survey on Various Disease Prediction Techniques</b> An analysis of various diseases have been predicted using multiple data mining and text mining techniques. In this article we are going to discuss about 6 prediction techniques. Using gene expression pattern we predict the disease outcome and implementation of pathway based approach for classifying disease based on hyper box principles, we also present a novel hybrid prediction model with missing value imputation HPM MI which analyze imputation using simple k means clustering. A technique based on CCAR Constraint Class Association Rule has been used for reducing time consumption in prediction of a particular disease. We have discussed about text mining technique and their applications. Another technique has also been studied about hyper triglyceride mia from anthropometric measures which diverge according to age and gender. Using multilayer classifiers for disease prediction we can achieve high diagnosis accuracy and high performance. Prediction, Genes, Data Mining, Text Mining, Hyper triglyceride mi a, Missing Values, Hmv and Classifiers 734-737 Issue-6 Volume-2 C. Leancy Jannet | G. Sumalatha