If you have a vector of x and y values then you can use several functions to estimate B. The correct method to use depending on your definition of the error function. For example, if you want to estimate B by minimizing the MSE (mean square error) then use lsqcurvefit(). For example,
xdata = ...
ydata = ...
y = @(B, x) 6e17*B.*log((x+B)./B);
B_estmated = lsqcurvefit(y, 1, xdata, ydata);
^ initial point for the numerical optimization algorithm.
Similarly, if you have some other error function, then you can use fmincon().