Progressive increase in the scientific methods of journal citation has prompted to the increase in\r\nimportance of journal metrics. Apart from Impact Factor, CiteScore is becoming increasingly\r\nimportant in the context of evaluating metrics for all journals. CiteScore is a simple way of\r\nmeasuring the citation impact of serial titles such as journals. A dataset of 667 journals were\r\nselected and regression analysis written in R resulted in r2 0.7266. Data was inspected for\r\noutliers prior regression analysis and identified 31 data points belonging outside the sphere. A\r\nnew regression after removing outliers resulted in better correlation coefficients and hence data\r\nwas divided into 624 training dataset and 12 data points as validation setbased on hierarchical\r\nclustering. This resulted in r2 0.7534 and r02 0.6753. Parameter values in Eq. 2 suggests that a\r\npositive value contributes positively towards better citescore of any journal under study. A\r\nmarginal increase in percentile value contributes positively towards increase in citescore value. If\r\nan increase in the volume of authors citing papers in any journal is increased, then the value of\r\ncitescore shoots up. Similarly, an increment in values of citation counts, SNIP and SJR increases\r\ncitescore.

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