This paper incorporates the adaptive neurofuzzy inference system (ANFIS) technique to model the yield of bio‐oil. The estimation of this parameter was performed according to pyrolysis conditions and biomass compositions of feedstock. For this purpose, this paper innovates two optimization methods including a genetic algorithm (GA) and particle swarm optimization (PSO). Primary data were gathered from previous studies and included 244 data of biodiesel oils. The findings showed a coefficient determination (R2) of 0.937 and RMSE of 2.1053 for the GA‐ANFIS model, and a coefficient determination (R2) of 0.968 and RMSE of 1.4443 for PSO‐ANFIS. This study indicates the capability of the PSO‐ANFIS algorithm in the estimation of the bio‐oil yield. According to the performed analysis, this model shows a higher ability than the previously presented models in predicting the target values and can be a suitable alternative to time‐consuming and difficult experimental tests.