Huge amount of banana peel biomass are generated annually which are excellent sources of bioenergy, biofuels and other value-added products. The initial moisture content of banana peel is about 70%, which leads to deterioration and limits the efficiency of conversion processes. Solar energy is abundant, free and renewable, so the solar drying of banana peel was investigated. Drying kinetics of banana peel in passive and active solar dryers were compared with that of direct sunlight. Mathematical and artificial neural network (ANN) modelling methods were applied to describe the rate of drying of the peel. The banana peel dried fastest in the active dryer followed by the passive dryer, then direct sunlight. The peels dried in the falling rate period. The Verma, Midilli-Kucuk and Weibull models best described the peel drying kinetics in direct sunlight, passive and active solar dryers, respectively. Feed-forward multilayer perception ANNs having (4-3-1) network topologies best fitted the drying data. The estimated diffusivities of moisture in the peel were 7.835 × 10-11, 9.59 × 10-11 and 1.952 × 10-10 m2 s-1 during its drying in direct sunlight, passive and active solar dryers, respectively. Renewable solar energy can sustainably remove moisture from banana peel biomass. Keywords: ANN Modelling, Banana peel, drying kinetics, mathematical modelling, solar dryer, thin layer