Parameter (θ ) estimation is the main question in regression, as it allows the rational analysis and comparison of data sets and experiments. Yet the knowledge of θ is often not sufficient for rational analysis, as the best fit values may differ for several performed experiments. The confidence interval of a parameter θ i estimates the range [θ i,-, θ i,+ ], within which the true parameter θi can be expected. However, the standard approach used in (multiple) linear regression cannot be applied for non-linear problems. SupraFit provides two basic routes to approximate the confidence interval, both being described in the literature before. Explicit references will be given in each section. One of the goals of this article and SupraFit regarding the statistical tools is not to have one correct way to calculate confidence intervals, but rather present the already known techniques, provide an easy way to access those and show some examples on how these methods can be applied to parameter estimation problems.