In Asian countries, small two-wheelers form a major share of the automobile segment and contribute significantly to carbon dioxide (CO2) emissions. Hybrid drives, though not widely applied in two-wheelers, can reduce fuel consumption and CO2 emissions. In this work three hybrid topologies, viz., P2 (electric motor placed between engine and transmission), P3 (electric motor placed between transmission and final drive), and power-split concepts (with planetary gear-train) have been modeled in Simulink, and their fuel consumption and emissions under the World Motorcycle Test Cycle (WMTC) have been evaluated. A physics-based model for the Continuously Variable Transmission (CVT) was used which is capable of predicting its transient characteristics. A map-based fuel consumption model and a Neural Network (NN)-based transient emission model were used for the engine. The NN-based transient emission model avoids the need to model the air path and fuel path in transient conditions, which is time consuming. The fueling characteristics of the Engine Control Unit (ECU) in transients need not be known if an NN model is built and tuned with sufficient experimental data. Several transient experiments were performed with speed-load profiles similar to the WMTC for tuning the NN emission models. Simulation results show that the P2 hybrid, P3 hybrid, and power-split drives have fuel economy benefits of about 27%, 37%, and 49%, respectively, compared to the conventional powertrain. However, nitrogen oxides (NOx) emissions are much higher for the hybrid powertrains due to the operation of the engine at higher load ranges for efficiency but are still within the prevailing BS6 Indian emission limits. A significant portion of the wheel energy input can be recovered through efficient regenerative braking in the WMTC. This will be even more significant under peak traffic city driving conditions. The belt losses in the CVT significantly reduce the potential benefits of the hybrid powertrain, and hence, an efficient transmission to replace it will be beneficial.