diff --git a/Documentation/CHANGELOG.md b/Documentation/CHANGELOG.md
index 49b860a50..e2593eca6 100644
--- a/Documentation/CHANGELOG.md
+++ b/Documentation/CHANGELOG.md
@@ -12,8 +12,9 @@ For more information on HARK, see [our Github organization](https://github.com/e
 
 Release Date: TBD
 
-#### Major Changes
+### Major Changes
 
+- Adds a discretize method to DBlocks and RBlocks (#1460)[https://github.com/econ-ark/HARK/pull/1460]
 - Allows structural equations in model files to be provided in string form [#1427](https://github.com/econ-ark/HARK/pull/1427)
 - Introduces `HARK.parser' module for parsing configuration files into models [#1427](https://github.com/econ-ark/HARK/pull/1427)
 
diff --git a/HARK/model.py b/HARK/model.py
index 1816460fd..19c8df296 100644
--- a/HARK/model.py
+++ b/HARK/model.py
@@ -2,7 +2,8 @@
 Tools for crafting models.
 """
 
-from dataclasses import dataclass, field
+from dataclasses import dataclass, field, replace
+from copy import copy, deepcopy
 from HARK.distribution import (
     Distribution,
     DiscreteDistributionLabeled,
@@ -135,8 +136,12 @@ def simulate_dynamics(
     return vals
 
 
+class Block:
+    pass
+
+
 @dataclass
-class DBlock:
+class DBlock(Block):
     """
     Represents a 'block' of model behavior.
     It prioritizes a representation of the dynamics of the block.
@@ -162,6 +167,26 @@ class DBlock:
     dynamics: dict = field(default_factory=dict)
     reward: dict = field(default_factory=dict)
 
+    def discretize(self, disc_params):
+        """
+        Returns a new DBlock which is a copy of this one, but with shock discretized.
+        """
+
+        disc_shocks = {}
+
+        for shockn in self.shocks:
+            if shockn in disc_params:
+                disc_shocks[shockn] = self.shocks[shockn].discretize(
+                    **disc_params[shockn]
+                )
+            else:
+                disc_shocks[shockn] = deepcopy(self.shocks[shockn])
+
+        # replace returns a modified copy
+        new_dblock = replace(self, shocks=disc_shocks)
+
+        return new_dblock
+
     def __post_init__(self):
         for v in self.dynamics:
             if isinstance(self.dynamics[v], str):
@@ -261,7 +286,7 @@ def mod_dvf(shock_value_array):
 
 
 @dataclass
-class RBlock:
+class RBlock(Block):
     """
     A recursive block.
 
@@ -272,7 +297,24 @@ class RBlock:
 
     name: str = ""
     description: str = ""
-    blocks: List[DBlock] = field(default_factory=list)
+    blocks: List[Block] = field(default_factory=list)
+
+    def discretize(self, disc_params):
+        """
+        Recursively discretizes all the blocks.
+        It replaces any DBlocks with new blocks with discretized shocks.
+        """
+        cbs = copy(self.blocks)
+
+        for i, b in list(enumerate(cbs)):
+            if isinstance(b, DBlock):
+                nb = b.discretize(disc_params)
+                cbs[i] = nb
+            elif isinstance(b, RBlock):
+                b.discretize(disc_params)
+
+        # returns a copy of the RBlock with the blocks replaced
+        return replace(self, blocks=cbs)
 
     def get_shocks(self):
         ### TODO: Bug in here is causing AttributeError: 'set' object has no attribute 'draw'
diff --git a/HARK/tests/test_model.py b/HARK/tests/test_model.py
index f5b2db434..ad14fe27e 100644
--- a/HARK/tests/test_model.py
+++ b/HARK/tests/test_model.py
@@ -1,6 +1,6 @@
 import unittest
 
-from HARK.distribution import Bernoulli
+from HARK.distribution import Bernoulli, DiscreteDistribution
 import HARK.model as model
 from HARK.model import Control
 import HARK.models.consumer as cons
@@ -44,6 +44,11 @@ def setUp(self):
     def test_init(self):
         self.assertEqual(self.test_block_A.name, "test block A")
 
+    def test_discretize(self):
+        dbl = self.cblock.discretize({"theta": {"N": 5}})
+
+        self.assertEqual(len(dbl.shocks["theta"].pmv), 5)
+
     def test_transition(self):
         post = self.cblock.transition(self.dpre, self.dr)
 
@@ -79,6 +84,8 @@ def setUp(self):
         self.test_block_C = model.DBlock(**test_block_C_data)
         self.test_block_D = model.DBlock(**test_block_D_data)
 
+        self.cpp = cons.cons_portfolio_problem
+
     def test_init(self):
         r_block_tree = model.RBlock(
             blocks=[
@@ -89,3 +96,13 @@ def test_init(self):
 
         r_block_tree.get_shocks()
         self.assertEqual(len(r_block_tree.get_shocks()), 3)
+
+    def test_discretize(self):
+        cppd = self.cpp.discretize({"theta": {"N": 5}, "risky_return": {"N": 6}})
+
+        self.assertEqual(len(cppd.get_shocks()["theta"].pmv), 5)
+        self.assertEqual(len(cppd.get_shocks()["risky_return"].pmv), 6)
+
+        self.assertFalse(
+            isinstance(self.cpp.get_shocks()["theta"], DiscreteDistribution)
+        )