Climate　change　is　a　multidimensional　phenomenon,　which　has　various　effects　on　people＇s　environmental　and　socioeconomic　conditions.　In　the　agricultural　economy　that　is　susceptible　to　natural　changes,　its　impact　is　more　profound.　Therefore,　climate　change　directly　affects　society　in　different　ways,　and　society　must　pay　a　price.　Climate　change,　especially　the　changes　in　annual　temperature　and　rainfall,　has　attracted　widespread　attention　worldwide.　The　variability　of　these　factors　or　the　magnitude　of　fluctuations　varies　according　to　location.　Therefore,　in　the　context　of　climate　change,　especially　in　countries　dominated　by　rainfed　agriculture,　studying　the　trend　of　meteorological　variables　is　essential　to　assess　climate-induced　variations　and　propose　feasible　adaptation　approaches.　Focusing　on　this　fact　is　the　main　goal　of　this　research　study　was　to　determine　the　rainfall　trend　and　the　accuracy　of　predicted　temperature　at　three　particular　stations　of　Khyber　Pakhtunkhwa　(Kp)　Province,　Pakistan.　For　this　purpose,　rainfall　and　temperature　data　were　provided　by　Pakistan　Meteorological　Department　(PMD),　Islamabad,　for　the　period　1960–2020.　Two　types　of　nonparametric　techniques,　Sen’s　slope　estimate　and　the　Mann–Kendall　test,　were　applied　to　determine　a　trend　in　the　average　monthly　and　annual　rainfall.　The　results　of　the　annual　rainfall　trend　analysis　showed　that　Peshawar　and　Dera　Ismail　Khan　stations　showed　a　positive　increasing　trend,　while　the　monthly　rainfall　trend　showed　a　negative　decreasing　trend　for　all　stations.　The　trend　was　statistically　significant　for　Peshawar　and　Saidu　Sharif　stations.　The　accuracy　of　predicted　and　actual　temperature　and　rainfall　indicated　that　mostly　over-forecast　occurred　at　Saidu　Sharif　and　Peshawar.　Most　of　the　precipitation　and　temperature　records　showed　under　forecast　for　Dera　Ismail　Khan,　but　some　over-prediction　has　also　occurred.　Graphical　abstract:　[Figure　not　available:　see　fulltext.]　©　2021,　The　Author(s).