This study analyses climate change farm-level adaptation measure among soybean farmers in Benue state, Nigeria. The study used multistage sampling technique and primary data were collected from 217 soybean farmers. Objective (i) was realized using descriptive statistics, viz. percentages and frequencies. Objective (ii) was achieved using stochastic frontier model. Objective (iii) made use of multivariate discreet choice model (MNL). Objective (v) was realized using Factor Analysis model (FA). Results of the multinomial logit analysis showed that Age positively influenced the use of crop diversification at 5% significant. Household size had positive relationship with the choice of crop diversification as farm-level adaptation measures. Farm size had a negative effect on the choice of multiple crop varieties. The stochastic frontier analysis showed that farm size was highly significant at 1% level of probability among soybean farmers. The computed mean of technical efficiency estimate was 0.12 and 0.90. The technical inefficiency model showed that land fragmentation (i.e. multiple farm plots) is significant at 5%, off farm employment is significant at 1%, both organic and inorganic had 10% significant technical inefficiency. The factor analysis revealed that the major constraints to climate change and farm-level adaptation measures among the soybean farmers were public, institutional and technological constraints; land, traditional beliefs and farm distance constraints; high cost of inputs, small scale production and knowledge of cropping or building resilience constraints; The study, therefore, recommends, inter alia, proactive regulatory land use systems that will make soybean farmers to participate in cooperative membership, have access to extension services to enhance their investment in climate change farm-level adaptation measures that has a long-term effect. More also, Government and non-governmental organizations should help the farmers in the area of provision and/ or facilitate the provision of input-based farm-level adaptation measure in the study area. Again, intensive use of already proven adaptation measures at farm-level by the farmers at their present resource technology will make them to reduce technical inefficiencies in the study area.