Forensic autopsy focuses on revealing the cause of death (CoD) by examination of a dead body. In this research study, various feature extraction schemes, feature value representation schemes and text classification algorithms have been applied on forensic autopsy reports to discover the suitable feature extraction approach, feature value representation approach and text classification approach. From experimental results, it was found that the unigram features outperformed bigram, trigram and hybrids of unigram, bigram and trigram features. Moreover, TF and TFiDF feature value representation schemes were proven more suitable than binary representation and normalized TFiDF schemes. Finally, SVM decision models outperformed RF and NB.