I have two random variables, $X, Y$ and their joint pdf, $f_{XY}(x,y )$.
I am able to find the marginal PDFs, $f_X(x)$ and $f_Y(y)$ using $f_X(x) = \int_{-\infty}^{\infty}f_{XY}(x,y)dy$ and similar for $f_Y(y)$.
Now I am given a new random variable: $Z = g(X, Y) = X - Y$
I found $f_Z(z)$ by first finding $F_Z(z)$ and taking its derivative with respect to $z$
$$ \begin{align} F_Z(z) = \mathbb{P}(Z \le z) \\ = \mathbb{P}(X - Y \le z) \\ = \mathbb{P}(Y \ge X - z) \\ = 1 - \mathbb{P}(Y \le X - z) \\ = 1 - \iint{f_{XY}(x,y)dydx} \end{align} $$ (The limits of integration in double integral are functions of $z$ (or constants).)
Then $f_Z(z) = \frac{d}{dz}F_Z(z)$
Now I need to find some conditional probabilities, such as $\mathbb{P}(X - Y > a | Y < a)$ and $\mathbb{P}(X - Y = b | Y < a)$.
Here is where I am stuck. If they were "simple" conditionals without a function of $X$ and $Y$, e.g., $\mathbb{P}(X < b|Y < a)$, I could just find the conditional pdf $f_{X|Y}(x|y) = \frac{f_{XY}(x,y)}{f_Y(y)}$ since I know the joint pdf of $X$ and $Y$ and the marginal pdfs.
But how would I proceed to find $\mathbb{P}(X - Y > a | Y < a)$? Is there some way to find a joint PDF of $Z$ (which is $X - Y$) and $Y$?