diff --git a/DESCRIPTION b/DESCRIPTION
index 3a90eb87..dc2009c6 100644
--- a/DESCRIPTION
+++ b/DESCRIPTION
@@ -68,7 +68,7 @@ VignetteBuilder:
     knitr
 Encoding: UTF-8
 Language: en-US
-RoxygenNote: 7.2.3.9000
+RoxygenNote: 7.3.0
 Config/testthat/edition: 3
 Config/testthat/parallel: true
 Roxygen: list(markdown = TRUE)
diff --git a/R/estimate_means.R b/R/estimate_means.R
index 7f2d27b1..222fa8a6 100644
--- a/R/estimate_means.R
+++ b/R/estimate_means.R
@@ -7,8 +7,6 @@
 #'
 #' @inheritParams get_emmeans
 #' @inheritParams parameters::model_parameters.default
-#' @param backend Whether to use 'emmeans' or 'marginaleffects' as a backend.
-#'  The latter is experimental and some features might not work.
 #' @inherit estimate_slopes details
 #'
 #' @examplesIf require("emmeans", quietly = TRUE)
@@ -51,10 +49,10 @@ estimate_means <- function(model,
                            fixed = NULL,
                            transform = "response",
                            ci = 0.95,
-                           backend = "emmeans",
+                          #  backend = "emmeans",
                            ...) {
   # Compute means
-  if (backend == "emmeans") {
+  # if (backend == "emmeans") {
     estimated <- get_emmeans(model, at, fixed, transform = transform, ...)
 
     # Summarize and clean
@@ -72,11 +70,7 @@ estimate_means <- function(model,
     means <- means[names(means) != "1"]
 
     info <- attributes(estimated)
-  } else {
-    means <- .get_marginalmeans(model, at, fixed, transform = transform, ...)
-
-    info <- attributes(means)
-  }
+  # }
 
   # Restore factor levels
   means <- datawizard::data_restoretype(means, insight::get_data(model))
diff --git a/R/get_marginalcontrasts.R b/R/get_marginalcontrasts.R
deleted file mode 100644
index d2d9edc8..00000000
--- a/R/get_marginalcontrasts.R
+++ /dev/null
@@ -1,65 +0,0 @@
-# Wrapper around marginaleffects to get marginal means
-#
-# library(modelbased)
-# if (require("marginaleffects")) {
-#
-# # Frequentist models
-# # -------------------
-# model <- lm(Petal.Length ~ Sepal.Width * Species, data = iris)
-#
-# estimate_means(model)
-# estimate_means(model, fixed = "Sepal.Width")
-# estimate_means(model, at = c("Species", "Sepal.Width"), length = 2)
-# estimate_means(model, at = "Species=c('versicolor', 'setosa')")
-# estimate_means(model, at = "Sepal.Width=c(2, 4)")
-# estimate_means(model, at = c("Species", "Sepal.Width=0"))
-# estimate_means(model, at = "Sepal.Width", length = 5)
-# estimate_means(model, at = "Sepal.Width=c(2, 4)")
-#
-# # Methods that can be applied to it:
-# means <- estimate_means(model, fixed = "Sepal.Width")
-# if (require("see")) {
-#   plot(means) # which runs visualisation_recipe()
-# }
-# standardize(means)
-#
-# if (require("lme4")) {
-#   data <- iris
-#   data$Petal.Length_factor <- ifelse(data$Petal.Length < 4.2, "A", "B")
-#
-#   model <- lmer(Petal.Length ~ Sepal.Width + Species + (1 | Petal.Length_factor), data = data)
-#  estimate_means(model)
-#   estimate_means(model, at = "Sepal.Width", length = 3)
-# }
-# }
-# }
-# #' @keywords internal
-# .get_marginalmeans <- function(model,
-#                                at = "auto",
-#                                fixed = NULL,
-#                                transform = "response",
-#                                ci = 0.95,
-#                                ...) {
-#
-#   # check if available
-#   insight::check_if_installed("marginaleffects")
-#
-#   # Guess arguments
-#   args <- modelbased:::.guess_emmeans_arguments(model, at, fixed, ...)
-#
-#   # Run emmeans
-#   means <- marginaleffects::marginalmeans(model, args$at, conf_level = ci)
-#
-#   # Format names
-#   names(means)[names(means) %in% c("conf.low")] <- "CI_low"
-#   names(means)[names(means) %in% c("conf.high")] <- "CI_high"
-#   names(means)[names(means) %in% c("std.error")] <- "SE"
-#   names(means)[names(means) %in% c("marginalmean")] <- "Mean"
-#   names(means)[names(means) %in% c("p.value")] <- "p"
-#   names(means)[names(means) %in% c("statistic")] <- "p"
-#
-#   ifelse(insight::find_statistic(model) == "t-statistic", "t", "statistic")
-#
-#   out
-#
-# }
diff --git a/R/get_marginalmeans.R b/R/get_marginalmeans.R
deleted file mode 100644
index bd62f426..00000000
--- a/R/get_marginalmeans.R
+++ /dev/null
@@ -1,42 +0,0 @@
-#' @keywords internal
-.get_marginalmeans <- function(model,
-                               at = "auto",
-                               fixed = NULL,
-                               transform = "response",
-                               ci = 0.95,
-                               ...) {
-  # check if available
-  insight::check_if_installed("marginaleffects")
-
-  # Guess arguments
-  args <- .guess_emmeans_arguments(model, at, fixed, ...)
-
-  # Run emmeans
-  means <- marginaleffects::marginalmeans(model, variables = args$at, conf_level = ci)
-
-  # TODO: this should be replaced by parameters::parameters(means)
-  # Format names
-  names(means)[names(means) %in% "conf.low"] <- "CI_low"
-  names(means)[names(means) %in% "conf.high"] <- "CI_high"
-  names(means)[names(means) %in% "std.error"] <- "SE"
-  names(means)[names(means) %in% "marginalmean"] <- "Mean"
-  names(means)[names(means) %in% "p.value"] <- "p"
-  names(means)[names(means) %in% "statistic"] <- ifelse(insight::find_statistic(model) == "t-statistic", "t", "statistic")
-
-  # Format terms
-  term <- unique(means$term) # Get name of variable
-  if (length(term) > 1L) {
-    insight::format_error("marignalmeans backend can currently only deal with one 'at' variable.")
-  }
-  names(means)[names(means) %in% c("value")] <- term # Replace 'value' col by var name
-  means$term <- NULL
-
-  # Drop stats
-  means$p <- NULL
-  means$t <- NULL
-
-  # Store attributes
-  attr(means, "at") <- args$at
-
-  means
-}
diff --git a/man/estimate_means.Rd b/man/estimate_means.Rd
index 840663cb..e21f33ef 100644
--- a/man/estimate_means.Rd
+++ b/man/estimate_means.Rd
@@ -10,7 +10,6 @@ estimate_means(
   fixed = NULL,
   transform = "response",
   ci = 0.95,
-  backend = "emmeans",
   ...
 )
 }
@@ -38,9 +37,6 @@ probabilities.}
 
 \item{ci}{Confidence Interval (CI) level. Default to \code{0.95} (\verb{95\%}).}
 
-\item{backend}{Whether to use 'emmeans' or 'marginaleffects' as a backend.
-The latter is experimental and some features might not work.}
-
 \item{...}{Other arguments passed for instance to \code{\link[insight:get_datagrid]{insight::get_datagrid()}}.}
 }
 \value{
diff --git a/man/modelbased-package.Rd b/man/modelbased-package.Rd
index 6ad16b23..d2e92fe2 100644
--- a/man/modelbased-package.Rd
+++ b/man/modelbased-package.Rd
@@ -3,7 +3,6 @@
 \docType{package}
 \name{modelbased-package}
 \alias{modelbased-package}
-\alias{_PACKAGE}
 \alias{modelbased}
 \title{modelbased: Estimation of Model-Based Predictions, Contrasts and Means}
 \description{
diff --git a/tests/testthat/test-get_marginalmeans.R b/tests/testthat/test-get_marginalmeans.R
deleted file mode 100644
index dda20c9a..00000000
--- a/tests/testthat/test-get_marginalmeans.R
+++ /dev/null
@@ -1,12 +0,0 @@
-test_that("get_marginaleffects", {
-  skip_if_not_installed("marginaleffects")
-  skip_if_not_installed("lme4")
-  model <- lm(Sepal.Width ~ Species * Petal.Length, data = iris)
-
-  estimated <- suppressMessages(estimate_means(model, backend = "marginaleffects"))
-
-  expect_equal(nrow(estimated), 3)
-  expect_true(ncol(estimated) >= 5)
-
-  # get_marginaleffects(model, trend = "Petal.Length", at = "Species", length = 10)
-})