process. Process capability indices the essential techniques in statistical quality control (SQC) for comparing and estimating the characteristics of the process to desired specifications. Most manufacturer certification included the decision based in the line of action capability analysis and followed the suitable procedure for constructing process capability index. Existing process capability indices based on normality assumption and the robust methods apply as the case maybe non-normal data. This study is the comparative study of process capability index and process capability index for Gamma distribution. In this research, three different bootstrap confidence intervals (BCI’s) are investigated with various Gamma distribution parameters. The proposed techniques are standard, percentile, and bias corrected bootstrap confidence intervals. In the simulation study has been done in R software. The average width of the bootstrap confidence intervals (BCI’s) has been calculated for three different techniques. The width (average) of bias-corrected BSI provides a minimum value from the other two techniques. A confidence interval is a statistical range that estimates a population parameter using a sample from the population. The bootstrapping method entails generating multiple new datasets by resampling the original data, with the goal of estimating parameters. By creating a new data set, it becomes possible to estimate the empirical distribution for the parameter.