diff --git a/CHANGELOG.md b/CHANGELOG.md
index 405c20923..6d393fe31 100644
--- a/CHANGELOG.md
+++ b/CHANGELOG.md
@@ -8,6 +8,10 @@ Remember to align the itemized text with the first line of an item within a list
 
 ## jax 0.4.26
 
+* New Functionality
+  * Added {func}`jax.numpy.trapezoid`, following the addition of this function in
+    NumPy 2.0.
+
 * Deprecations & Removals
   * {func}`jax.tree_map` is deprecated; use `jax.tree.map` instead, or for backward
     compatibility with older JAX versions, use {func}`jax.tree_util.tree_map`.
diff --git a/docs/jax.numpy.rst b/docs/jax.numpy.rst
index cdc557477..41c87603b 100644
--- a/docs/jax.numpy.rst
+++ b/docs/jax.numpy.rst
@@ -391,6 +391,7 @@ namespace; they are listed below.
     tensordot
     tile
     trace
+    trapezoid
     transpose
     tri
     tril
diff --git a/jax/_src/numpy/lax_numpy.py b/jax/_src/numpy/lax_numpy.py
index 1fdda450e..36175fa9a 100644
--- a/jax/_src/numpy/lax_numpy.py
+++ b/jax/_src/numpy/lax_numpy.py
@@ -2877,6 +2877,27 @@ def repeat(a: ArrayLike, repeats: ArrayLike, axis: int | None = None, *,
   return take(a, gather_indices, axis=axis)
 
 
+@util.implements(getattr(np, "trapezoid", getattr(np, "trapz", None)))
+@partial(jit, static_argnames=('axis',))
+def trapezoid(y: ArrayLike, x: ArrayLike | None = None, dx: ArrayLike = 1.0,
+              axis: int = -1) -> Array:
+  # TODO(phawkins): remove this annotation after fixing jnp types.
+  dx_array: Array
+  if x is None:
+    util.check_arraylike('trapezoid', y)
+    y_arr, = util.promote_dtypes_inexact(y)
+    dx_array = asarray(dx)
+  else:
+    util.check_arraylike('trapezoid', y, x)
+    y_arr, x_arr = util.promote_dtypes_inexact(y, x)
+    if x_arr.ndim == 1:
+      dx_array = diff(x_arr)
+    else:
+      dx_array = moveaxis(diff(x_arr, axis=axis), axis, -1)
+  y_arr = moveaxis(y_arr, axis, -1)
+  return 0.5 * (dx_array * (y_arr[..., 1:] + y_arr[..., :-1])).sum(-1)
+
+
 @util.implements(np.tri)
 def tri(N: int, M: int | None = None, k: int = 0, dtype: DTypeLike | None = None) -> Array:
   dtypes.check_user_dtype_supported(dtype, "tri")
diff --git a/jax/_src/scipy/integrate.py b/jax/_src/scipy/integrate.py
index 97cfe0ff1..e60d8a06b 100644
--- a/jax/_src/scipy/integrate.py
+++ b/jax/_src/scipy/integrate.py
@@ -27,18 +27,4 @@ import jax.numpy as jnp
 @partial(jit, static_argnames=('axis',))
 def trapezoid(y: ArrayLike, x: ArrayLike | None = None, dx: ArrayLike = 1.0,
               axis: int = -1) -> Array:
-  # TODO(phawkins): remove this annotation after fixing jnp types.
-  dx_array: Array
-  if x is None:
-    util.check_arraylike('trapezoid', y)
-    y_arr, = util.promote_dtypes_inexact(y)
-    dx_array = jnp.asarray(dx)
-  else:
-    util.check_arraylike('trapezoid', y, x)
-    y_arr, x_arr = util.promote_dtypes_inexact(y, x)
-    if x_arr.ndim == 1:
-      dx_array = jnp.diff(x_arr)
-    else:
-      dx_array = jnp.moveaxis(jnp.diff(x_arr, axis=axis), axis, -1)
-  y_arr = jnp.moveaxis(y_arr, axis, -1)
-  return 0.5 * (dx_array * (y_arr[..., 1:] + y_arr[..., :-1])).sum(-1)
+  return jnp.trapezoid(y, x, dx, axis)
diff --git a/jax/numpy/__init__.py b/jax/numpy/__init__.py
index 72b2ed7f9..273c5a2aa 100644
--- a/jax/numpy/__init__.py
+++ b/jax/numpy/__init__.py
@@ -233,6 +233,7 @@ from jax._src.numpy.lax_numpy import (
     tensordot as tensordot,
     tile as tile,
     trace as trace,
+    trapezoid as trapezoid,
     transpose as transpose,
     tri as tri,
     tril as tril,
@@ -447,7 +448,15 @@ from jax._src.numpy.array_methods import register_jax_array_methods
 register_jax_array_methods()
 del register_jax_array_methods
 
-try:
-  from numpy import issubsctype as _deprecated_issubsctype
-except ImportError:
-  _deprecated_issubsctype = None
+
+_deprecations = {
+  # Deprecated 18 Sept 2023 and removed 06 Feb 2024
+  "trapz": (
+    "jnp.trapz is deprecated; use jnp.trapezoid instead.",
+    None
+  ),
+}
+
+from jax._src.deprecations import deprecation_getattr as _deprecation_getattr
+__getattr__ = _deprecation_getattr(__name__, _deprecations)
+del _deprecation_getattr
diff --git a/jax/numpy/__init__.pyi b/jax/numpy/__init__.pyi
index a618f4570..9ed5f39b3 100644
--- a/jax/numpy/__init__.pyi
+++ b/jax/numpy/__init__.pyi
@@ -788,6 +788,8 @@ def tile(A: ArrayLike, reps: Union[DimSize, Sequence[DimSize]]) -> Array: ...
 def trace(a: ArrayLike, offset: int = ..., axis1: int = ..., axis2: int = ...,
           dtype: Optional[DTypeLike] = ..., out: None = ...) -> Array: ...
 def transpose(a: ArrayLike, axes: Optional[Sequence[int]] = ...) -> Array: ...
+def trapezoid(y: ArrayLike, x: ArrayLike | None = None, dx: ArrayLike = ...,
+              axis: int = ...) -> Array: ...
 def tri(
     N: int, M: Optional[int] = ..., k: int = ..., dtype: DTypeLike = ...
 ) -> Array: ...
diff --git a/tests/lax_numpy_test.py b/tests/lax_numpy_test.py
index ed3a16eda..6aa8fb9d8 100644
--- a/tests/lax_numpy_test.py
+++ b/tests/lax_numpy_test.py
@@ -5571,6 +5571,37 @@ class LaxBackedNumpyTests(jtu.JaxTestCase):
       numpy_result = np.isdtype(dtype, kind)
       self.assertEqual(jax_result, numpy_result)
 
+  @jtu.sample_product(
+    [dict(yshape=yshape, xshape=xshape, dx=dx, axis=axis)
+      for yshape, xshape, dx, axis in [
+        ((10,), None, 1.0, -1),
+        ((3, 10), None, 2.0, -1),
+        ((3, 10), None, 3.0, -0),
+        ((10, 3), (10,), 1.0, -2),
+        ((3, 10), (10,), 1.0, -1),
+        ((3, 10), (3, 10), 1.0, -1),
+        ((2, 3, 10), (3, 10), 1.0, -2),
+      ]
+    ],
+    dtype=float_dtypes + int_dtypes,
+  )
+  @jtu.skip_on_devices("tpu")  # TODO(jakevdp): fix and reenable this test.
+  @jax.numpy_rank_promotion('allow')  # This test explicitly exercises implicit rank promotion.
+  def test_trapezoid(self, yshape, xshape, dtype, dx, axis):
+    rng = jtu.rand_default(self.rng())
+    args_maker = lambda: [rng(yshape, dtype), rng(xshape, dtype) if xshape is not None else None]
+    if jtu.numpy_version() >= (2, 0, 0):
+      np_fun = partial(np.trapezoid, dx=dx, axis=axis)
+    else:
+      np_fun = partial(np.trapz, dx=dx, axis=axis)
+    jnp_fun = partial(jnp.trapezoid, dx=dx, axis=axis)
+    tol = jtu.tolerance(dtype, {np.float16: 2e-3, np.float64: 1e-12,
+                                jax.dtypes.bfloat16: 4e-2})
+    self._CheckAgainstNumpy(np_fun, jnp_fun, args_maker, tol=tol,
+                            check_dtypes=False)
+    self._CompileAndCheck(jnp_fun, args_maker, atol=tol, rtol=tol,
+                          check_dtypes=False)
+
 
 # Most grad tests are at the lax level (see lax_test.py), but we add some here
 # as needed for e.g. particular compound ops of interest.