The sequential probability ratio test is a powerful statistical tool that is frequently employed for hypothesis testing, parameter estimation, and statistical inference. The aspect of robustness is of utmost importance when employing SPRTS in practical applications. Past studies have investigated the robustness of SPRTS for specific distributions. We have developed SPRTS for a family of inverse distributions that includes eleven distinct distributions. The primary objective of this study is to investigate and evaluate the robustness of SPRTS under various conditions and distributions, focusing on the parameters of the inverse distribution family. SPRTS efficacy is measured using OC and ASN functions. This study comprehensively covers the construction and rigorous evaluation of SPRTS, particularly in testing simple null hypotheses against simple alternative hypotheses. Additionally, we investigate the robustness of SPRTS under various factors, including the presence of other parameters and specified coefficients of variation. Conclusive results, graphic representations, tables, and acceptance and rejection regions add clarity to the findings.