How to obtain parameter estimates of a model using maximum likelihood estimation?

I have a model (P = B0 + B1*Acc), where p = probability of decision (between 0 & 1), B0 and B1 are parameters to be estimated using MLE and Acc is independent variable (values ranging from -5 to +5). I have used built-in function of "mle" of MATLAB for log-logistic distribution and it is returning mu and sigma value. Using mu & sigma values, I can calculate the f(x) for log-logistic distribution but I am confused that whether that f(x) would give probability (P) same as above model? What about B0 n B1? Model goodness-of-fit (likelihood ratio)? Can anyone help me in sorting out my issue?