diff --git a/NEWS.md b/NEWS.md
index 50544dcce6..8a31cd598a 100644
--- a/NEWS.md
+++ b/NEWS.md
@@ -1,7 +1,6 @@
 # ggplot2 (development version)
 
-* A function can be provided to `labs(alt = <...>)` that takes the plot as input
-  and returns text as output (@teunbrand, #4795).
+* `stat_ecdf()` now has an optional `weight` aesthetic (@teunbrand, #5058).
 * Position scales combined with `coord_sf()` can now use functions in the 
  `breaks` argument. In addition, `n.breaks` works as intended and 
  `breaks = NULL` removes grid lines and axes (@teunbrand, #4622).
diff --git a/R/stat-ecdf.R b/R/stat-ecdf.R
index 5f7e5fdd30..fc55dc2e04 100644
--- a/R/stat-ecdf.R
+++ b/R/stat-ecdf.R
@@ -12,6 +12,10 @@
 #' and one of them must be unused. The ECDF will be calculated on the given aesthetic
 #' and will be output on the unused one.
 #'
+#' If the `weight` aesthetic is provided, a weighted ECDF will be computed. In
+#' this case, the ECDF is incremented by `weight / sum(weight)` instead of
+#' `1 / length(x)` for each observation.
+#'
 #' @inheritParams layer
 #' @inheritParams geom_point
 #' @param na.rm If `FALSE` (the default), removes missing values with
@@ -20,10 +24,16 @@
 #'   of points to interpolate with.
 #' @param pad If `TRUE`, pad the ecdf with additional points (-Inf, 0)
 #'   and (Inf, 1)
+#' @eval rd_aesthetics("stat", "ecdf")
 #' @eval rd_computed_vars(
 #'   ecdf = "Cumulative density corresponding to `x`.",
 #'   y    = "`r lifecycle::badge('superseded')` For backward compatibility."
 #' )
+#' @section Dropped variables:
+#' \describe{
+#'   \item{weight}{After calculation, weights of individual observations (if
+#'     supplied), are no longer available.}
+#' }
 #' @export
 #' @examples
 #' set.seed(1)
@@ -41,6 +51,17 @@
 #' # Multiple ECDFs
 #' ggplot(df, aes(x, colour = g)) +
 #'   stat_ecdf()
+#'
+#' # Using weighted eCDF
+#' weighted <- data.frame(x = 1:10, weights = c(1:5, 5:1))
+#' plain <- data.frame(x = rep(weighted$x, weighted$weights))
+#'
+#' ggplot(plain, aes(x)) +
+#'   stat_ecdf(linewidth = 1) +
+#'   stat_ecdf(
+#'     aes(weight = weights),
+#'     data = weighted, colour = "green"
+#'   )
 stat_ecdf <- function(mapping = NULL, data = NULL,
                       geom = "step", position = "identity",
                       ...,
@@ -74,7 +95,7 @@ stat_ecdf <- function(mapping = NULL, data = NULL,
 StatEcdf <- ggproto("StatEcdf", Stat,
   required_aes = c("x|y"),
 
-  default_aes = aes(x = after_stat(ecdf), y = after_stat(ecdf)),
+  default_aes = aes(x = after_stat(ecdf), y = after_stat(ecdf), weight = NULL),
 
   setup_params = function(self, data, params) {
     params$flipped_aes <- has_flipped_aes(data, params, main_is_orthogonal = FALSE, main_is_continuous = TRUE)
@@ -100,7 +121,7 @@ StatEcdf <- ggproto("StatEcdf", Stat,
     if (pad) {
       x <- c(-Inf, x, Inf)
     }
-    data_ecdf <- stats::ecdf(data$x)(x)
+    data_ecdf <- wecdf(data$x, data$weight)(x)
 
     df_ecdf <- data_frame0(
       x = x,
@@ -110,6 +131,63 @@ StatEcdf <- ggproto("StatEcdf", Stat,
     )
     df_ecdf$flipped_aes <- flipped_aes
     flip_data(df_ecdf, flipped_aes)
-  }
+  },
+
+  dropped_aes = "weight"
 )
 
+# Weighted eCDF function
+wecdf <- function(x, weights = NULL) {
+
+  weights <- weights %||% 1
+  weights <- vec_recycle(weights, length(x))
+
+  # Sort vectors
+  ord <- order(x, na.last = NA)
+  x <- x[ord]
+  weights <- weights[ord]
+
+  if (any(!is.finite(weights))) {
+    cli::cli_warn(c(paste0(
+      "The {.field weight} aesthetic does not support non-finite or ",
+      "{.code NA} values."
+    ), "i" = "These weights were replaced by {.val 0}."))
+    weights[!is.finite(weights)] <- 0
+  }
+
+  # `total` replaces `length(x)`
+  total <- sum(weights)
+
+  if (abs(total) < 1000 * .Machine$double.eps) {
+    if (total == 0) {
+      cli::cli_abort(paste0(
+        "Cannot compute eCDF when the {.field weight} aesthetic sums up to ",
+        "{.val 0}."
+      ))
+    }
+    cli::cli_warn(c(
+      "The sum of the {.field weight} aesthetic is close to {.val 0}.",
+      "i" = "Computed eCDF might be unstable."
+    ))
+  }
+
+  # Link each observation to unique value
+  vals <- unique0(x)
+  matched <- match(x, vals)
+
+  # Instead of tabulating `matched`, as we would for unweighted `ecdf(x)`,
+  # we sum weights per unique value of `x`
+  agg_weights <- vapply(
+    split(weights, matched),
+    sum, numeric(1)
+  )
+
+  # Like `ecdf(x)`, we return an approx function
+  approxfun(
+    vals,
+    cumsum(agg_weights) / total,
+    method = "constant",
+    yleft = 0, yright = 1,
+    f = 0, ties = "ordered"
+  )
+}
diff --git a/man/stat_ecdf.Rd b/man/stat_ecdf.Rd
index 2a8e6c80e7..d0941b2b56 100644
--- a/man/stat_ecdf.Rd
+++ b/man/stat_ecdf.Rd
@@ -125,7 +125,22 @@ The statistic relies on the aesthetics assignment to guess which variable to
 use as the input and which to use as the output. Either x or y must be provided
 and one of them must be unused. The ECDF will be calculated on the given aesthetic
 and will be output on the unused one.
+
+If the \code{weight} aesthetic is provided, a weighted ECDF will be computed. In
+this case, the ECDF is incremented by \code{weight / sum(weight)} instead of
+\code{1 / length(x)} for each observation.
+}
+\section{Aesthetics}{
+
+\code{stat_ecdf()} understands the following aesthetics (required aesthetics are in bold):
+\itemize{
+\item \strong{\code{\link[=aes_position]{x}} \emph{or} \code{\link[=aes_position]{y}}}
+\item \code{\link[=aes_group_order]{group}}
+\item \code{weight}
+}
+Learn more about setting these aesthetics in \code{vignette("ggplot2-specs")}.
 }
+
 \section{Computed variables}{
 
 These are calculated by the 'stat' part of layers and can be accessed with \link[=aes_eval]{delayed evaluation}.
@@ -135,6 +150,14 @@ These are calculated by the 'stat' part of layers and can be accessed with \link
 }
 }
 
+\section{Dropped variables}{
+
+\describe{
+\item{weight}{After calculation, weights of individual observations (if
+supplied), are no longer available.}
+}
+}
+
 \examples{
 set.seed(1)
 df <- data.frame(
@@ -151,4 +174,15 @@ ggplot(df, aes(x)) +
 # Multiple ECDFs
 ggplot(df, aes(x, colour = g)) +
   stat_ecdf()
+
+# Using weighted eCDF
+weighted <- data.frame(x = 1:10, weights = c(1:5, 5:1))
+plain <- data.frame(x = rep(weighted$x, weighted$weights))
+
+ggplot(plain, aes(x)) +
+  stat_ecdf(linewidth = 1) +
+  stat_ecdf(
+    aes(weight = weights),
+    data = weighted, colour = "green"
+  )
 }
diff --git a/tests/testthat/test-stat-ecdf.R b/tests/testthat/test-stat-ecdf.R
index 6fd8297e18..399dfbebb0 100644
--- a/tests/testthat/test-stat-ecdf.R
+++ b/tests/testthat/test-stat-ecdf.R
@@ -15,6 +15,54 @@ test_that("stat_ecdf works in both directions", {
   expect_snapshot_error(ggplot_build(p))
 })
 
+test_that("weighted ecdf computes sensible results", {
+
+  set.seed(42)
+  x <- rpois(100, 5)
+  ux <- sort(unique0(x))
+
+  # Absent weights should be the same as the original
+  expect_equal(
+    ecdf(x)(ux),
+    wecdf(x, NULL)(ux)
+  )
+
+  # Uniform weights should be the same as the original
+  expect_equal(
+    ecdf(x)(ux),
+    wecdf(x, pi)(ux)
+  )
+
+  # Tabulated weights should be the same as the original
+  tab   <- as.data.frame(table(x), stringsAsFactors = FALSE)
+  tab$x <- as.numeric(tab$x)
+  expect_equal(
+    ecdf(x)(ux),
+    wecdf(tab$x, tab$Freq)(ux)
+  )
+})
+
+test_that("weighted ecdf warns about weird weights", {
+
+  # Should warn when provided with illegal weights
+  expect_warning(
+    wecdf(1:10, c(NA, rep(1, 9))),
+    "does not support non-finite"
+  )
+
+  # Should warn when provided with near-0 weights
+  expect_warning(
+    wecdf(1:10, .Machine$double.eps),
+    "might be unstable"
+  )
+
+  # Should error when weights sum to 0
+  expect_error(
+    wecdf(1:10, rep(c(-1, 1), 5)),
+    "Cannot compute eCDF"
+  )
+})
+
 # See #5113 and #5112
 test_that("stat_ecdf responds to axis transformations", {
   n <- 4