Rainfall　is　a　climatic　factor　that　affects　many　human　activities　like　agriculture,　construction,　and　forestry.　Rainfall　is　dependent　on　various　meteorological　features　and　its　prediction　is　a　very　complex　task　due　to　the　dynamic　climatic　nature.　A　detailed　study　of　different　climatic　features　associated　with　the　occurrence　of　rainfall　should　be　made　in　order　to　understand　the　influence　of　each　parameter　in　the　context　of　rainfall.　In　this　paper,　we　propose　a　methodical　approach　to　analyze　the　affect　of　various　parameters　on　rainfall.　Our　study　uses　5　years　of　meteorological　data　from　a　weather　station　located　in　the　United　States.　The　correlation　and　interdependence　among　the　collected　meteorological　features　were　obtained.　Additionally,　we　identified　the　most　important　meteorological　features　for　rainfall　prediction　using　a　machine　learning-based　feature　selection　technique.