Virtual　prototyping　tools　are　widely　used　in　the　development　of　new　motorcycles,　but　the　instability　of　two-wheel　vehicles　leads　to　the　necessity　of　implementing　a　vehicle　driver.　In　this　brief,　the　development　of　an　effective　virtual　rider　(VR)　is　described　that　is　capable　of　controlling　the　motorcycle　during　complex,　high　performance　maneuvers.　The　control　inputs　are　the　steering　angle,　the　lateral　rider　movement,　and　the　throttle/braking　effort.　The　proposed　motorcycle　model　consists　of　a　plane　that　can　roll　and　slide　(both　in　x　-　and　y-directions),　on　which　a　moving　point　mass　with　lateral　degree　of　freedom　(DoF)　is　attached,　representing　the　rider.　The　controller　is　designed　within　the　nonlinear　model　predictive　control　(MPC)　framework.　The　implementation　is　developed　in　MATMPC,　an　open-source　toolbox,　and　tested　in　co-simulation　with　the　commercial　software　VI-BikeRealTime,　specifically　designed　to　reproduce　vehicles　behavior　with　high　fidelity.　A　chicane　and　a　lap　on　a　challenging　track　have　been　used　to　both　show　flexibility　and　evaluate　performance,　demonstrating　the　capability　of　the　proposed　VR　of　handling　complex　maneuvers.