Climate change has an impact on decreasing agricultural production, especially food crops. The rate of decline in agricultural production due to climate change ranges from 5-20%.The objective of this study was to forecastfood-cropsat Papua Province that are tolerance and adaptable to climate change using trend method. This study used four models of trend analysis, i.e: linear least square pattern, quadratic, exponential, and moving averages, with secondary data base of rice, maize, soybean and sweet potato production; climate data (rainfall); productivity and harvested areas from 1970-2015. These data were used to estimate food crop production in the year of climate change to determine their impact on food-crop production. Results showed that soybean was the most sensitive crop to climate change. It has the biggest impact on production, yield declined on both El Nino (10.7%) and La Nina (11.4%). The lowest impact was on rice crop, which is generally cultivated on the wetlands, El Nino decreased of production of 2.9% and La Nina increased production 2.4%, respectively. Two other crops, maize production decreased 7.4% on the El Nino and 3.9% increased during the La Nina. Futhermore, the the analysis revealed that sweet potatois the most resistant crop to climate change since it production increase by 2.5% during El Nino. As conclusion, moving average trendof order 2 model was most appropriate to estimate the value of rice and soybean production in the 1970-2015 period.The quadratictrend model wasapropriate to estimate maize and sweet potato production based on its the MAPE, MAD, and MSD values.