  We study the extreme value statistics of first-passage trajectories
generating from a one-dimensional drifted Brownian motion subject to stochastic
resetting to the starting point with a constant rate $r$. Each stochastic
trajectory starts from a positive position $x_0$ and terminates whenever the
particle hits the origin for the first time. \textcolor{blue}{We obtain the
exact expression for the marginal distribution $P_r(M|x_0)$ of the maximum
displacement $M$}. We find that stochastic resetting has a profound impact on
$P_r(M|x_0)$ and the expected value $\langle M \rangle$ of $M$. Depending on
the drift velocity $v$, $\langle M \rangle$ shows three distinct trends of
change with $r$. For $v \geq 0$, $\langle M \rangle$ decreases monotonically
with $r$, and tends to $2x_0$ as $r \to \infty$. For $v_c<v<0$, $\langle M
\rangle$ shows a nonmonotonic dependence on $r$, in which a minimum $\langle M
\rangle$ exists for an intermediate level of $r$. For $v\leq v_c$, $\langle M
\rangle$ increases monotonically with $r$. Moreover, by deriving the propagator
and using path decomposition technique, we obtain in the Laplace domain the
joint distribution of $M$ and the time $t_m$ at which the maximum $M$ is
reached. Interestingly, the dependence of the expected value $\langle t_m
\rangle$ of $t_m$ on $r$ is either monotonic or nonmonotonic, depending on the
value of $v$. For $v>v_m$, there is a nonzero resetting rate at which $\langle
t_m \rangle$ attains its minimum. Otherwise, $\langle t_m \rangle$ increases
monotonically with $r$. We provide an analytical determination of two critical
values of $v$, $v_c\approx -1.69415 D/x_0$ and $v_m\approx -1.66102 D/x_0$,
where $D$ is the diffusion constant. Finally, numerical simulations are
performed to support our theoretical results.
