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Hazard rate is known as the instantaneous probability of default at time t. It is of much use in numerous areas including finance, actuarial sciences, medicine and many more. The topic of estimating hazard rate function for different statistical distributions under various scenarios has received great attention in the literature. Depending on complete and censored sample structures, the estimation procedure changes. In this talk, we will show how the hazard rate function is estimated under these sampling schemes when the underlying distributions are assumed to have some unknown parameters. Moreover, the difference between the estimation of monotonic and non-monotonic hazard rate functions will be discussed. Some real life applications will also be presented during the talk.