Computerisation of Statistical methods and application have created positive impact in research and implementation of decisions in Mathematics.Considering this, the current review explains various applications of the generalized additive model (GAM) as used in GAM fitting function, gam, which returns an object of the class “gam”, which can be further analysed using method functions such as print, anova, summary, plot, residuals, predict etc. Through modification of data of the average Science scores by country from the Programme for International Student Assessment(PISA) 2006, along with GNI per capita (Purchasing Power Parity, 2005dollars), Educational Index, Health Index, and Human Development Index from UN data cite{''2006''} and importing it into R we show how a generalised additive model explains the relationship between average Science scores in various countries and the different predictor variables; using the functions in the mgcv package