Abstract: Fiducial distribution for a parameter is essentially the posterior distribution with no prior distribution on the parameter.  In this talk, we shall describe Fisher's method of finding a fiducial distribution for a parameter and fiducial inference through examples involving well-known distributions such as the normal and binomial. We then describe the approach for finding fiducial distributions for the parameters of a location-scale family. In particular, we shall see fiducial methods for finding confidence intervals, prediction intervals, prediction limits for the mean of a future sample and one-sided tolerance limits in one-way random models. Application to analysis of zero-inflated lognormal data will also be discussed. All the methods will be illustrated using some practical examples.