You need at least one more data point to do a standard regression, so that you have more equations than unknowns.
Even with more points, it is possible that the regression equation will predict negative reflectance for some combinatons of R, G, B. If you want a model that will never give values outside [0,1], then you need a nonlinear model. You could take the linear prediction and apply a hard or smooth limit funciton to it. Suppose your linear model is rinit=a*R+b*G+c*B. The code below shows final reflectance, rfinal, computed with hard and smooth limits.
rinit=-1:.05:2;
rfinalH=min(max(rinit,0),1);
rfinalS=exp(4*(rinit-.5))./(1+exp(4*(rinit-.5)));
plot(rinit,rfinalH,'rx-',rinit,rfinalS,'bo-');
xlabel('Linear Reflectance Prediction'); grid on;
ylabel('Final Reflectance'); legend('Hard','Soft');
Try it.
