Built on the hints in Dap's answer. Basically mimicking the proof for the Open Mapping Theorem.
Note: here the statement "$\text{Ran}(A)$ is of the Second Category" must be understood as "$\text{Ran}(A)$, equipped with the subspace topology, is a Second Category space". It should not be understood as being a Second Category subset of $Y$.
Proof. Firstly, the closure of the range $\overline{\text{Ran}(A)}$, with its subspace topology, is a Banach space. By the Baire Category Theorem, it is of Second Category. Also, the subspace topology of $\text{Ran}(A)$, inherited from $Y$, coincides with that inherited from the closure $\overline{\text{Ran}(A)}$. If $\text{Ran}(A)$ is a Second Category space, it is then a Second Category subset in Banach space $\overline{\text{Ran}(A)}$. Hence, since
$$\text{Ran}(A)=\cup_{n\in\mathbb{N}}A(nB_X(1))=\cup_{n\in\mathbb{N}}nA(B_X(1)),$$
there exists $n_0\in\mathbb{N}$ such that $\text{Int} \overline{n_0 A(B_X(1))}\neq \emptyset$ in terms of the subspace topology of $\overline{\text{Ran}(A)}$. Then there exists some $r_0>0$ and $y_0\in Y$ such that
$B_Y(y_0, r_0)\cap\overline{\text{Ran}(A)} \subset \overline{n_0 A(B_X(1))}.$
It can therefore be shown that, for every $L>0$,
$B_Y(\frac{r_0}{2n_0}L)\cap \overline{\text{Ran}(A)}\subset \overline{A(B_X(L))}.$
So for every $y\in \overline{\text{Ran}(A)}\setminus\{0\}$, we have $y\in \overline{B_Y(\|y\|_Y)}\cap \overline{\text{Ran}(A)}\subset \overline{A(B_X(\frac{2n_0}{r_0}\|y\|_Y))}$. That is, there exists $x\in B_X(\frac{2n_0}{r_0}\|y\|_Y)$ such that $\|y-Ax\|_Y<\frac{\|y\|_Y}{2}$. But this means
$$y-Ax\in B_Y(\frac{\|y\|_Y}{2})\cap \overline{\text{Ran}(A)}\subset \overline{A(B_X(\frac{2n_0}{r_0}\frac{\|y\|_Y}{2}))}.$$
Hence, we can inductively choose a sequence $(x_n)_{n\in\mathbb{N}}$ in $X$ satisfying $\|x_n\|_X< \frac{2n_0}{r_0}\frac{\|y\|_Y}{2^{n-1}}$ and
$$\|y-A(x_1+\cdots +x_n)\|_Y<\frac{\|y\|_Y}{2^{n-1}}.$$
Hence, by the completeness of $X$, $\sum_n x_n$ converges absolutely to some $\xi\in X$. By continuity of $A$, taking the limit gives
$0_Y=\lim_{n\to\infty}(y-A(x_1+\cdots +x_n))=y-A\xi,$
and so $y=A\xi\in \text{Ran}(A)$.
Hence $\text{Ran}(A)=\overline{\text{Ran}(A)}$ is closed. $\square$