The scientific output of researchers has become an important achievement in scientific community. In most recent years, several bibliographic indices were proposed to assess the quality of the academic research publications, h-index being more prominent among all indices. Considering h-index value of a journal as dependent variable and citation parameters as independent variables, a python based regression algorithmic approach was reported in this study to delineate the dependency of h-index on citation parameters such as Total Docs., Total Cites, Citable Docs., Cites/Doc. and Ref./Doc., respectively. From regression analysis, it is observed that high value of TC3, CD3 and CD2 contributes positively to enhance h-index factor of journals, whereas on the other hand, TD3 and RD would contribute negatively to hindex.