Is there a method to convert two estimates that have been calculated using linear regression, to a percentage?

eg, I have two X scores, two corresponding estimated Y scores, and a standard error of estimate.

Is it valid to say a given X will score higher than another given X, a specified percentage of the time?

I guess to rephrase the question...

Is there a way to calculate the percentage likelihood that the true value of the estimate for a given X score will be larger than that for another given X score?

i.e %chance that Y¹ > Y² for given X¹ and X²

example data:

X¹ is predicted as Y¹= 50

X² is predicted as Y² = 60

Standard error of estimate = 10

so, 95% of the time the true value of Y¹ will be between 30 and 70.

and 95% of the time the true value of Y² will be between 40-80.

What would be the percentage chance that Y¹ will be higher than Y², or vice versa?

(Assuming we ignore the other 5%, or so, of the time).

I've tried working it out manually, and its doing my head in..

Eg, I can work out using only 1 std deviation, ie, 65% of the time, that, for the give figures above, Y¹ will be higher than Y² 25% of the time, and therefore Y² will be higher 75% of the time... but taking it to 2 std devs gets more complicated, and I'm sure there's some sort of confidence interval equation I could be using.

I do realise that the 65% of the time is for one Y value only, however, for brevity, I'm ignoring that that figure applies to all X's..

Hope this makes sense, and any help or suggestions appreciated.