The purpose of this project is to shed some light on how the MGCV(Mixed GAM Computational Vehicle) package in R is used in generalized additive modelling. A generalized additive model (GAM) is a generalized linear model in which the linear predictor depends linearly on unknown smooth functions of some predictor variables, and interest focuses on inference about these smooth functions (Wikipedia). The MGCV package is loaded with the main 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 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.